http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/MatrixBase.scala ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/MatrixBase.scala b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/MatrixBase.scala new file mode 100644 index 0000000..00823b6 --- /dev/null +++ b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/MatrixBase.scala @@ -0,0 +1,75 @@ +/** + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.mahout.viennacl.openmp.javacpp + +import org.bytedeco.javacpp.Pointer +import org.bytedeco.javacpp.annotation._ + +import scala.collection.mutable.ArrayBuffer + + +@Properties(inherit = Array(classOf[Context]), + value = Array(new Platform( + library = "jniViennaCL" + ))) +@Name(Array("viennacl::matrix_base<double>")) +class MatrixBase extends Pointer { + + protected val ptrs = new ArrayBuffer[Pointer]() + + override def deallocate(deallocate: Boolean): Unit = { + super.deallocate(deallocate) + ptrs.foreach(_.close()) + } + + @Name(Array("operator=")) + @native def :=(@Const @ByRef src: DenseRowMatrix) + + @Name(Array("operator=")) + @native def :=(@Const @ByRef src: DenseColumnMatrix) + + @Name(Array("size1")) + @native + def nrow: Int + + @Name(Array("size2")) + @native + def ncol: Int + + @Name(Array("row_major")) + @native + def isRowMajor: Boolean + + @Name(Array("internal_size1")) + @native + def internalnrow: Int + + @Name(Array("internal_size2")) + @native + def internalncol: Int + + @Name(Array("memory_domain")) + @native + def memoryDomain: Int + + @Name(Array("switch_memory_context")) + @native + def switchMemoryContext(@ByRef ctx: Context) + + + +}
http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/MemHandle.scala ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/MemHandle.scala b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/MemHandle.scala new file mode 100644 index 0000000..938a262 --- /dev/null +++ b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/MemHandle.scala @@ -0,0 +1,34 @@ +/** + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.mahout.viennacl.openmp.javacpp + +import org.bytedeco.javacpp.Pointer +import org.bytedeco.javacpp.annotation._ + + +@Properties(inherit = Array(classOf[Context]), + value = Array(new Platform( + library = "jniViennaCL") + )) +@Namespace("viennacl::backend") +@Name(Array("mem_handle")) +class MemHandle extends Pointer { + + allocate() + + @native def allocate() +} http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/ProdExpression.scala ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/ProdExpression.scala b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/ProdExpression.scala new file mode 100644 index 0000000..315a03c --- /dev/null +++ b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/ProdExpression.scala @@ -0,0 +1,33 @@ +/** + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.mahout.viennacl.openmp.javacpp + +import org.bytedeco.javacpp.Pointer +import org.bytedeco.javacpp.annotation.{Name, Namespace, Platform, Properties} + + +@Properties(inherit = Array(classOf[Context]), + value = Array(new Platform( + library = "jniViennaCL") + )) +@Namespace("viennacl") +@Name(Array("matrix_expression<const viennacl::compressed_matrix<double>, " + + "const viennacl::compressed_matrix<double>, " + + "viennacl::op_prod>")) +class ProdExpression extends Pointer { + +} http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/SrMatDnMatProdExpression.scala ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/SrMatDnMatProdExpression.scala b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/SrMatDnMatProdExpression.scala new file mode 100644 index 0000000..e9c7bac --- /dev/null +++ b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/SrMatDnMatProdExpression.scala @@ -0,0 +1,33 @@ +/** + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.mahout.viennacl.openmp.javacpp + +import org.bytedeco.javacpp.Pointer +import org.bytedeco.javacpp.annotation.{Name, Namespace, Platform, Properties} + + +@Properties(inherit = Array(classOf[Context]), + value = Array(new Platform( + library = "jniViennaCL") + )) +@Namespace("viennacl") +@Name(Array("matrix_expression<const viennacl::compressed_matrix<double>, " + + "const viennacl::matrix_base<double>, " + + "viennacl::op_prod>")) +class SrMatDnMatProdExpression extends Pointer { + +} http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/VCLVector.scala ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/VCLVector.scala b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/VCLVector.scala new file mode 100644 index 0000000..33947ec --- /dev/null +++ b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/VCLVector.scala @@ -0,0 +1,124 @@ +package org.apache.mahout.viennacl.openmp.javacpp + +import org.bytedeco.javacpp._ +import org.bytedeco.javacpp.annotation._ + + +@Properties(inherit = Array(classOf[Context]), + value = Array(new Platform( + library="jniViennaCL" + ))) +@Name(Array("viennacl::vector<double>")) +final class VCLVector(defaultCtr: Boolean = true) extends VectorBase { + + if (defaultCtr) allocate() + + def this(){ + this(false) + allocate() + } + + def this(size: Int) { + this(false) + allocate(size, new Context(Context.MAIN_MEMORY)) + } + + def this(size: Int, ctx: Context ) { + this(false) + allocate(size, ctx) + } + + def this(@Const @ByRef ve: VecMultExpression) { + this(false) + allocate(ve) + } + + def this(@Const @ByRef vmp: MatVecProdExpression) { + this(false) + allocate(vmp) + } + +// conflicting with the next signature as MemHandle is a pointer and so is a DoublePointer.. +// leave out for now. +// +// def this(h: MemHandle , vec_size: Int, vec_start: Int = 0, vec_stride: Int = 1) { +// this(false) +// allocate(h, vec_size, vec_start, vec_stride) +// } + + def this(ptr_to_mem: DoublePointer, + @Cast(Array("viennacl::memory_types"))mem_type : Int, + vec_size: Int) { + + this(false) + allocate(ptr_to_mem, mem_type, vec_size, 0, 1) + ptrs += ptr_to_mem + } + + def this(ptr_to_mem: DoublePointer, + @Cast(Array("viennacl::memory_types"))mem_type : Int, + vec_size: Int, + start: Int, + stride: Int) { + + this(false) + allocate(ptr_to_mem, mem_type, vec_size, start, stride) + ptrs += ptr_to_mem + } + + def this(@Const @ByRef vc: VCLVector) { + this(false) + allocate(vc) + } + def this(@Const @ByRef vb: VectorBase) { + this(false) + allocate(vb) + } + + @native protected def allocate() + + @native protected def allocate(size: Int) + + @native protected def allocate(size: Int, @ByVal ctx: Context) + + @native protected def allocate(@Const @ByRef ve: VecMultExpression) + + @native protected def allocate(@Const @ByRef ve: MatVecProdExpression) + + @native protected def allocate(@Const @ByRef vb: VCLVector) + + @native protected def allocate(@Const @ByRef vb: VectorBase) + + +// @native protected def allocate(h: MemHandle , vec_size: Int, +// vec_start: Int, +// vec_stride: Int) + + @native protected def allocate(ptr_to_mem: DoublePointer, + @Cast(Array("viennacl::memory_types"))mem_type : Int, + vec_size: Int, + start: Int, + stride: Int) + + @Name(Array("viennacl::vector<double>::self_type")) + def selfType:VectorBase = this.asInstanceOf[VectorBase] + + + @native def switch_memory_context(@ByVal context: Context): Unit + +// Swaps the handles of two vectors by swapping the OpenCL handles only, no data copy. +// @native def fast_swap(@ByVal other: VCLVector): VectorBase + +// add this operator in for tests many more can be added +// @Name(Array("operator*")) +// @native @ByPtr def *(i: Int): VectorMultExpression + + + +} + +object VCLVector { + Context.loadLib() +} + + http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/VecMultExpression.scala ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/VecMultExpression.scala b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/VecMultExpression.scala new file mode 100644 index 0000000..7562de5 --- /dev/null +++ b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/VecMultExpression.scala @@ -0,0 +1,32 @@ +/** + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.mahout.viennacl.openmp.javacpp + +import org.bytedeco.javacpp.Pointer +import org.bytedeco.javacpp.annotation.{Name, Namespace, Platform, Properties} + + +@Properties(inherit = Array(classOf[Context]), + value = Array(new Platform( + library = "jniViennaCL") + )) +@Namespace("viennacl") +@Name(Array("vector_expression<const viennacl::vector_base<double>," + + "const double, viennacl::op_mult >")) +class VecMultExpression extends Pointer { + +} http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/VectorBase.scala ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/VectorBase.scala b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/VectorBase.scala new file mode 100644 index 0000000..8efd377 --- /dev/null +++ b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/javacpp/VectorBase.scala @@ -0,0 +1,55 @@ +/** + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.mahout.viennacl.openmp.javacpp + +import org.bytedeco.javacpp._ +import org.bytedeco.javacpp.annotation._ + +import scala.collection.mutable.ArrayBuffer + + +@Properties(inherit = Array(classOf[Context]), + value = Array(new Platform( + library="jniViennaCL" + ))) +@Name(Array("viennacl::vector_base<double>")) +class VectorBase extends Pointer { + + protected val ptrs = new ArrayBuffer[Pointer]() + + override def deallocate(deallocate: Boolean): Unit = { + super.deallocate(deallocate) + ptrs.foreach(_.close()) + } + + // size of the vec elements + @native @Const def size(): Int + + // size of the vec elements + padding + @native @Const def internal_size(): Int + + // handle to the vec element buffer + @native @Const @ByRef def handle: MemHandle + +// // add this operator in for tests many more can be added +// @Name(Array("operator* ")) +// @native def *(i: Int): VectorMultExpression + + +} + + http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/package.scala ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/package.scala b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/package.scala new file mode 100644 index 0000000..89af010 --- /dev/null +++ b/viennacl-omp/scala-2.10/src/main/scala/org/apache/mahout/viennacl/openmp/package.scala @@ -0,0 +1,434 @@ +package org.apache.mahout.viennacl + +import java.nio._ + +import org.apache.mahout.math._ +import scalabindings._ +import RLikeOps._ + +import scala.collection.JavaConversions._ +import org.apache.mahout.viennacl.openmp.javacpp.DenseRowMatrix +import org.apache.mahout.viennacl.openmp.javacpp._ +import org.bytedeco.javacpp.{DoublePointer, IntPointer} + + + +package object openmp { + + type IntConvertor = Int => Int + + def toVclDenseRM(src: Matrix, vclCtx: Context = new Context(Context.MAIN_MEMORY)): DenseRowMatrix = { + vclCtx.memoryType match { + case Context.MAIN_MEMORY â + val vclMx = new DenseRowMatrix( + data = repackRowMajor(src, src.nrow, src.ncol), + nrow = src.nrow, + ncol = src.ncol, + ctx = vclCtx + ) + vclMx + case _ â + val vclMx = new DenseRowMatrix(src.nrow, src.ncol, vclCtx) + fastCopy(src, vclMx) + vclMx + } + } + + + /** + * Convert a dense row VCL matrix to mahout matrix. + * + * @param src + * @return + */ + def fromVclDenseRM(src: DenseRowMatrix): Matrix = { + val nrowIntern = src.internalnrow + val ncolIntern = src.internalncol + + // A technical debt here: + + // We do double copying here, this is obviously suboptimal, but hopefully we'll compensate + // this with gains from running superlinear algorithms in VCL. + val dbuff = new DoublePointer(nrowIntern * ncolIntern) + Functions.fastCopy(src, dbuff) + var srcOffset = 0 + val ncol = src.ncol + val rows = for (irow â 0 until src.nrow) yield { + + val rowvec = new Array[Double](ncol) + dbuff.position(srcOffset).get(rowvec) + + srcOffset += ncolIntern + rowvec + } + + // Always! use shallow = true to avoid yet another copying. + new DenseMatrix(rows.toArray, true) + } + + def fastCopy(mxSrc: Matrix, dst: DenseRowMatrix) = { + val nrowIntern = dst.internalnrow + val ncolIntern = dst.internalncol + + assert(nrowIntern >= mxSrc.nrow && ncolIntern >= mxSrc.ncol) + + val rmajorData = repackRowMajor(mxSrc, nrowIntern, ncolIntern) + Functions.fastCopy(rmajorData, new DoublePointer(rmajorData).position(rmajorData.limit()), dst) + + rmajorData.close() + } + + private def repackRowMajor(mx: Matrix, nrowIntern: Int, ncolIntern: Int): DoublePointer = { + + assert(mx.nrow <= nrowIntern && mx.ncol <= ncolIntern) + + val dbuff = new DoublePointer(nrowIntern * ncolIntern) + + mx match { + case dm: DenseMatrix â + val valuesF = classOf[DenseMatrix].getDeclaredField("values") + valuesF.setAccessible(true) + val values = valuesF.get(dm).asInstanceOf[Array[Array[Double]]] + var dstOffset = 0 + for (irow â 0 until mx.nrow) { + val rowarr = values(irow) + dbuff.position(dstOffset).put(rowarr, 0, rowarr.size min ncolIntern) + dstOffset += ncolIntern + } + dbuff.position(0) + case _ â + // Naive copying. Could be sped up for a DenseMatrix. TODO. + for (row â mx) { + val dstOffset = row.index * ncolIntern + for (el â row.nonZeroes) dbuff.put(dstOffset + el.index, el) + } + } + + dbuff + } + + /** + * + * @param mxSrc + * @param ctx + * @return + */ + def toVclCmpMatrixAlt(mxSrc: Matrix, ctx: Context): CompressedMatrix = { + + // use repackCSR(matrix, ctx) to convert all ints to unsigned ints if Context is Ocl + // val (jumpers, colIdcs, els) = repackCSRAlt(mxSrc) + val (jumpers, colIdcs, els) = repackCSR(mxSrc, ctx) + + val compMx = new CompressedMatrix(mxSrc.nrow, mxSrc.ncol, els.capacity().toInt, ctx) + compMx.set(jumpers, colIdcs, els, mxSrc.nrow, mxSrc.ncol, els.capacity().toInt) + compMx + } + + private def repackCSRAlt(mx: Matrix): (IntPointer, IntPointer, DoublePointer) = { + val nzCnt = mx.map(_.getNumNonZeroElements).sum + val jumpers = new IntPointer(mx.nrow + 1L) + val colIdcs = new IntPointer(nzCnt + 0L) + val els = new DoublePointer(nzCnt) + var posIdx = 0 + + var sortCols = false + + // Row-wise loop. Rows may not necessarily come in order. But we have to have them in-order. + for (irow â 0 until mx.nrow) { + + val row = mx(irow, ::) + jumpers.put(irow.toLong, posIdx) + + // Remember row start index in case we need to restart conversion of this row if out-of-order + // column index is detected + val posIdxStart = posIdx + + // Retry loop: normally we are done in one pass thru it unless we need to re-run it because + // out-of-order column was detected. + var done = false + while (!done) { + + // Is the sorting mode on? + if (sortCols) { + + // Sorting of column indices is on. So do it. + row.nonZeroes() + // Need to convert to a strict collection out of iterator + .map(el â el.index â el.get) + // Sorting requires Sequence api + .toSeq + // Sort by column index + .sortBy(_._1) + // Flush to the CSR buffers. + .foreach { case (index, v) â + colIdcs.put(posIdx.toLong, index) + els.put(posIdx.toLong, v) + posIdx += 1 + } + + // Never need to retry if we are already in the sorting mode. + done = true + + } else { + + // Try to run unsorted conversion here, switch lazily to sorted if out-of-order column is + // detected. + var lastCol = 0 + val nzIter = row.nonZeroes().iterator() + var abortNonSorted = false + + while (nzIter.hasNext && !abortNonSorted) { + + val el = nzIter.next() + val index = el.index + + if (index < lastCol) { + + // Out of order detected: abort inner loop, reset posIdx and retry with sorting on. + abortNonSorted = true + sortCols = true + posIdx = posIdxStart + + } else { + + // Still in-order: save element and column, continue. + els.put(posIdx, el) + colIdcs.put(posIdx.toLong, index) + posIdx += 1 + + // Remember last column seen. + lastCol = index + } + } // inner non-sorted + + // Do we need to re-run this row with sorting? + done = !abortNonSorted + + } // if (sortCols) + + } // while (!done) retry loop + + } // row-wise loop + + // Make sure Mahout matrix did not cheat on non-zero estimate. + assert(posIdx == nzCnt) + + jumpers.put(mx.nrow.toLong, nzCnt) + + (jumpers, colIdcs, els) + } + + // same as repackCSRAlt except converts to jumpers, colIdcs to unsigned ints before setting + private def repackCSR(mx: Matrix, context: Context): (IntPointer, IntPointer, DoublePointer) = { + val nzCnt = mx.map(_.getNumNonZeroElements).sum + val jumpers = new IntPointer(mx.nrow + 1L) + val colIdcs = new IntPointer(nzCnt + 0L) + val els = new DoublePointer(nzCnt) + var posIdx = 0 + + var sortCols = false + + def convertInt: IntConvertor = if(context.memoryType == Context.OPENCL_MEMORY) { + int2cl_uint + } else { + i: Int => i: Int + } + + // Row-wise loop. Rows may not necessarily come in order. But we have to have them in-order. + for (irow â 0 until mx.nrow) { + + val row = mx(irow, ::) + jumpers.put(irow.toLong, posIdx) + + // Remember row start index in case we need to restart conversion of this row if out-of-order + // column index is detected + val posIdxStart = posIdx + + // Retry loop: normally we are done in one pass thru it unless we need to re-run it because + // out-of-order column was detected. + var done = false + while (!done) { + + // Is the sorting mode on? + if (sortCols) { + + // Sorting of column indices is on. So do it. + row.nonZeroes() + // Need to convert to a strict collection out of iterator + .map(el â el.index â el.get) + // Sorting requires Sequence api + .toIndexedSeq + // Sort by column index + .sortBy(_._1) + // Flush to the CSR buffers. + .foreach { case (index, v) â + // convert to cl_uint if context is OCL + colIdcs.put(posIdx.toLong, convertInt(index)) + els.put(posIdx.toLong, v) + posIdx += 1 + } + + // Never need to retry if we are already in the sorting mode. + done = true + + } else { + + // Try to run unsorted conversion here, switch lazily to sorted if out-of-order column is + // detected. + var lastCol = 0 + val nzIter = row.nonZeroes().iterator() + var abortNonSorted = false + + while (nzIter.hasNext && !abortNonSorted) { + + val el = nzIter.next() + val index = el.index + + if (index < lastCol) { + + // Out of order detected: abort inner loop, reset posIdx and retry with sorting on. + abortNonSorted = true + sortCols = true + posIdx = posIdxStart + + } else { + + // Still in-order: save element and column, continue. + els.put(posIdx, el) + // convert to cl_uint if context is OCL + colIdcs.put(posIdx.toLong, convertInt(index)) + posIdx += 1 + + // Remember last column seen. + lastCol = index + } + } // inner non-sorted + + // Do we need to re-run this row with sorting? + done = !abortNonSorted + + } // if (sortCols) + + } // while (!done) retry loop + + } // row-wise loop + + // Make sure Mahout matrix did not cheat on non-zero estimate. + assert(posIdx == nzCnt) + + // convert to cl_uint if context is OCL + jumpers.put(mx.nrow.toLong, convertInt(nzCnt)) + + (jumpers, colIdcs, els) + } + + + + def fromVclCompressedMatrix(src: CompressedMatrix): Matrix = { + val m = src.size1 + val n = src.size2 + val NNz = src.nnz + + val row_ptr_handle = src.handle1 + val col_idx_handle = src.handle2 + val element_handle = src.handle + + val row_ptr = new IntPointer((m + 1).toLong) + val col_idx = new IntPointer(NNz.toLong) + val values = new DoublePointer(NNz.toLong) + + Functions.memoryReadInt(row_ptr_handle, 0, (m + 1) * 4, row_ptr, false) + Functions.memoryReadInt(col_idx_handle, 0, NNz * 4, col_idx, false) + Functions.memoryReadDouble(element_handle, 0, NNz * 8, values, false) + + val rowPtr = row_ptr.asBuffer() + val colIdx = col_idx.asBuffer() + val vals = values.asBuffer() + + rowPtr.rewind() + colIdx.rewind() + vals.rewind() + + + val srMx = new SparseRowMatrix(m, n) + + // read the values back into the matrix + var j = 0 + // row wise, copy any non-zero elements from row(i-1,::) + for (i <- 1 to m) { + // for each nonzero element, set column col(idx(j) value to vals(j) + while (j < rowPtr.get(i)) { + srMx(i - 1, colIdx.get(j)) = vals.get(j) + j += 1 + } + } + srMx + } + + def toVclVec(vec: Vector, ctx: Context): VCLVector = { + + vec match { + case vec: DenseVector => { + val valuesF = classOf[DenseVector].getDeclaredField("values") + valuesF.setAccessible(true) + val values = valuesF.get(vec).asInstanceOf[Array[Double]] + val el_ptr = new DoublePointer(values.length.toLong) + el_ptr.put(values, 0, values.length) + + new VCLVector(el_ptr, ctx.memoryType, values.length) + } + + case vec: SequentialAccessSparseVector => { + val it = vec.iterateNonZero + val size = vec.size() + val el_ptr = new DoublePointer(size.toLong) + while (it.hasNext) { + val el: Vector.Element = it.next + el_ptr.put(el.index, el.get()) + } + new VCLVector(el_ptr, ctx.memoryType, size) + } + + case vec: RandomAccessSparseVector => { + val it = vec.iterateNonZero + val size = vec.size() + val el_ptr = new DoublePointer(size.toLong) + while (it.hasNext) { + val el: Vector.Element = it.next + el_ptr.put(el.index, el.get()) + } + new VCLVector(el_ptr, ctx.memoryType, size) + } + case _ => throw new IllegalArgumentException("Vector sub-type not supported.") + } + + } + + def fromVClVec(vclVec: VCLVector): Vector = { + val size = vclVec.size + val element_handle = vclVec.handle + val ele_ptr = new DoublePointer(size) + Functions.memoryReadDouble(element_handle, 0, size * 8, ele_ptr, false) + + // for now just assume its dense since we only have one flavor of + // VCLVector + val mVec = new DenseVector(size) + for (i <- 0 until size) { + mVec.setQuick(i, ele_ptr.get(i + 0L)) + } + + mVec + } + + + // TODO: Fix this? cl_uint must be an unsigned int per each machine's representation of such. + // this is currently not working anyways. + // cl_uint is needed for OpenCl sparse Buffers + // per https://www.khronos.org/registry/cl/sdk/1.1/docs/man/xhtml/scalarDataTypes.html + // it is simply an unsigned int, so strip the sign. + def int2cl_uint(i: Int): Int = { + ((i >>> 1) << 1) + (i & 1) + } + + +} http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.10/src/test/scala/org/apache/mahout/viennacl/omp/ViennaCLSuiteOMP.scala ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.10/src/test/scala/org/apache/mahout/viennacl/omp/ViennaCLSuiteOMP.scala b/viennacl-omp/scala-2.10/src/test/scala/org/apache/mahout/viennacl/omp/ViennaCLSuiteOMP.scala new file mode 100644 index 0000000..af29e3c --- /dev/null +++ b/viennacl-omp/scala-2.10/src/test/scala/org/apache/mahout/viennacl/omp/ViennaCLSuiteOMP.scala @@ -0,0 +1,249 @@ +package org.apache.mahout.viennacl.openmp + +import org.apache.mahout.math._ +import scalabindings._ +import RLikeOps._ +import org.bytedeco.javacpp.DoublePointer +import org.scalatest.{FunSuite, Matchers} +import org.apache.mahout.viennacl.openmp.javacpp._ +import org.apache.mahout.viennacl.openmp.javacpp.Functions._ +import org.apache.mahout.viennacl.openmp.javacpp.LinalgFunctions._ + +import scala.util.Random + +class ViennaCLSuiteOMP extends FunSuite with Matchers { + + test("row-major viennacl::matrix") { + + // Just to make sure the javacpp library is loaded: + Context.loadLib() + + val m = 20 + val n = 30 + val data = new DoublePointer(m * n) + val buff = data.asBuffer() + // Fill with some noise + while (buff.remaining() > 0) buff.put(Random.nextDouble()) + + // Create row-major matrix with OpenCL + val hostClCtx = new Context(Context.MAIN_MEMORY) + val cpuMx = new DenseRowMatrix(data = data, nrow = m, ncol = n, hostClCtx) + // And free. + cpuMx.close() + + } + + + test("mmul microbenchmark") { + val memCtx = new Context(Context.MAIN_MEMORY) + + val m = 3000 + val n = 3000 + val s = 1000 + + val r = new Random(1234) + + // Dense row-wise + val mxA = new DenseMatrix(m, s) + val mxB = new DenseMatrix(s, n) + + // add some data + mxA := { (_, _, _) => r.nextDouble() } + mxB := { (_, _, _) => r.nextDouble() } + + var ms = System.currentTimeMillis() + mxA %*% mxB + ms = System.currentTimeMillis() - ms + info(s"Mahout multiplication time: $ms ms.") + + import LinalgFunctions._ + + // openMP/cpu time, including copying: + { + ms = System.currentTimeMillis() + val ompA = toVclDenseRM(mxA, memCtx) + val ompB = toVclDenseRM(mxB, memCtx) + val ompC = new DenseRowMatrix(prod(ompA, ompB)) + val mxC = fromVclDenseRM(ompC) + ms = System.currentTimeMillis() - ms + info(s"ViennaCL/cpu/OpenMP multiplication time: $ms ms.") + + ompA.close() + ompB.close() + ompC.close() + } + + } + + test("trans") { + + val ompCtx = new Context(Context.MAIN_MEMORY) + + + val m = 20 + val n = 30 + + val r = new Random(1234) + + // Dense row-wise + val mxA = new DenseMatrix(m, n) + + // add some data + mxA := { (_, _, _) => r.nextDouble() } + + + // Test transposition in OpenMP + { + val ompA = toVclDenseRM(src = mxA, ompCtx) + val ompAt = new DenseRowMatrix(trans(ompA)) + + val mxAt = fromVclDenseRM(ompAt) + ompA.close() + ompAt.close() + + (mxAt - mxA.t).norm / m / n should be < 1e-16 + } + + } + + test("sparse mmul microbenchmark") { + + val ompCtx = new Context(Context.MAIN_MEMORY) + + val m = 3000 + val n = 3000 + val s = 1000 + + val r = new Random(1234) + + // sparse row-wise + val mxA = new SparseRowMatrix(m, s, false) + val mxB = new SparseRowMatrix(s, n, true) + + // add some sparse data with 20% density + mxA := { (_, _, v) => if (r.nextDouble() < .20) r.nextDouble() else v } + mxB := { (_, _, v) => if (r.nextDouble() < .20) r.nextDouble() else v } + + var ms = System.currentTimeMillis() + val mxC = mxA %*% mxB + ms = System.currentTimeMillis() - ms + info(s"Mahout Sparse multiplication time: $ms ms.") + + + // Test multiplication in OpenMP + { + ms = System.currentTimeMillis() + // val ompA = toVclCompressedMatrix(src = mxA, ompCtx) + // val ompB = toVclCompressedMatrix(src = mxB, ompCtx) + + val ompA = toVclCmpMatrixAlt(mxA, ompCtx) + val ompB = toVclCmpMatrixAlt(mxB, ompCtx) + + val ompC = new CompressedMatrix(prod(ompA, ompB)) + + ms = System.currentTimeMillis() - ms + info(s"ViennaCL/cpu/OpenMP Sparse multiplication time: $ms ms.") + + val ompMxC = fromVclCompressedMatrix(ompC) + (mxC - ompMxC).norm / mxC.nrow / mxC.ncol should be < 1e-10 + + ompA.close() + ompB.close() + ompC.close() + + } + + } + + test("VCL Dense Matrix %*% Dense vector - no OpenCl") { + + val ompCtx = new Context(Context.MAIN_MEMORY) + + + val m = 3000 + val s = 1000 + + val r = new Random(1234) + + // Dense row-wise + val mxA = new DenseMatrix(m, s) + val dvecB = new DenseVector(s) + + // add some random data + mxA := { (_,_,_) => r.nextDouble() } + dvecB := { (_,_) => r.nextDouble() } + + //test in matrix %*% vec + var ms = System.currentTimeMillis() + val mDvecC = mxA %*% dvecB + ms = System.currentTimeMillis() - ms + info(s"Mahout dense matrix %*% dense vector multiplication time: $ms ms.") + + + //Test multiplication in OpenMP + { + + ms = System.currentTimeMillis() + val ompMxA = toVclDenseRM(mxA, ompCtx) + val ompVecB = toVclVec(dvecB, ompCtx) + + val ompVecC = new VCLVector(prod(ompMxA, ompVecB)) + val ompDvecC = fromVClVec(ompVecC) + + ms = System.currentTimeMillis() - ms + info(s"ViennaCL/cpu/OpenMP dense matrix %*% dense vector multiplication time: $ms ms.") + (ompDvecC.toColMatrix - mDvecC.toColMatrix).norm / s should be < 1e-10 + + ompMxA.close() + ompVecB.close() + ompVecC.close() + } + + } + + + test("Sparse %*% Dense mmul microbenchmark") { + val memCtx = new Context(Context.MAIN_MEMORY) + + val m = 3000 + val n = 3000 + val s = 1000 + + val r = new Random(1234) + + // Dense row-wise + val mxSr = new SparseMatrix(m, s) + val mxDn = new DenseMatrix(s, n) + + // add some data + mxSr := { (_, _, v) => if (r.nextDouble() < .20) r.nextDouble() else v } + mxDn := { (_, _, _) => r.nextDouble() } + + var ms = System.currentTimeMillis() + mxSr %*% mxDn + ms = System.currentTimeMillis() - ms + info(s"Mahout multiplication time: $ms ms.") + + import LinalgFunctions._ + + + // openMP/cpu time, including copying: + { + ms = System.currentTimeMillis() + val ompA = toVclCmpMatrixAlt(mxSr, memCtx) + val ompB = toVclDenseRM(mxDn, memCtx) + val ompC = new DenseRowMatrix(prod(ompA, ompB)) + val mxC = fromVclDenseRM(ompC) + ms = System.currentTimeMillis() - ms + info(s"ViennaCL/cpu/OpenMP multiplication time: $ms ms.") + + ompA.close() + ompB.close() + ompC.close() + } + + } + + + +} http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.11/linux-haswell.properties ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.11/linux-haswell.properties b/viennacl-omp/scala-2.11/linux-haswell.properties new file mode 100644 index 0000000..3ee4494 --- /dev/null +++ b/viennacl-omp/scala-2.11/linux-haswell.properties @@ -0,0 +1,28 @@ +platform=linux-x86_64 +platform.path.separator=: +platform.source.suffix=.cpp +platform.includepath.prefix=-I +platform.includepath= +platform.compiler=g++ +platform.compiler.cpp11=-std=c++11 +platform.compiler.default= +platform.compiler.fastfpu=-msse3 -ffast-math +platform.compiler.viennacl=-fopenmp -fpermissive +platform.compiler.nodeprecated=-Wno-deprecated-declarations +#build for haswell arch with for GCC >= 4.9.0 +platform.compiler.output=-Wl,-rpath,$ORIGIN/ -Wl,-z,noexecstack -Wl,-Bsymbolic -march=haswell -m64 -Wall -O3 -fPIC -shared -s -o\u0020 +#for GCC < 4.9.0 use -march=core-avx2 for haswell arch +#platform.compiler.output=-Wl,-rpath,$ORIGIN/ -Wl,-z,noexecstack -Wl,-Bsymbolic -march=core-avx2 -m64 -Wall -Ofast -fPIC -shared -s -o\u0020 +#build for native: +#platform.compiler.output=-Wl,-rpath,$ORIGIN/ -Wl,-z,noexecstack -Wl,-Bsymbolic -march=native -m64 -Wall -Ofast -fPIC -shared -s -o\u0020 +platform.linkpath.prefix=-L +platform.linkpath.prefix2=-Wl,-rpath, +platform.linkpath= +platform.link.prefix=-l +platform.link.suffix= +platform.link= +platform.framework.prefix=-F +platform.framework.suffix= +platform.framework= +platform.library.prefix=lib +platform.library.suffix=.so http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.11/linux-x86_64-viennacl.properties ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.11/linux-x86_64-viennacl.properties b/viennacl-omp/scala-2.11/linux-x86_64-viennacl.properties new file mode 100644 index 0000000..e5de1fa --- /dev/null +++ b/viennacl-omp/scala-2.11/linux-x86_64-viennacl.properties @@ -0,0 +1,24 @@ +platform=linux-x86_64 +platform.path.separator=: +platform.source.suffix=.cpp +platform.includepath.prefix=-I +platform.includepath= +platform.compiler=g++ +platform.compiler.cpp11=-std=c++11 +platform.compiler.default= +platform.compiler.fastfpu=-msse3 -ffast-math +platform.compiler.viennacl=-fopenmp -fpermissive +platform.compiler.nodeprecated=-Wno-deprecated-declarations +# platform.compiler.output=-Wl,-rpath,$ORIGIN/ -Wl,-z,noexecstack -Wl,-Bsymbolic -march=x86-64 -m64 -Wall -O3 -fPIC -shared -s -o\u0020 +platform.compiler.output=-Wl,-rpath,$ORIGIN/ -Wl,-z,noexecstack -Wl,-Bsymbolic -march=native -m64 -Wall -Ofast -fPIC -shared -s -o\u0020 +platform.linkpath.prefix=-L +platform.linkpath.prefix2=-Wl,-rpath, +platform.linkpath= +platform.link.prefix=-l +platform.link.suffix= +platform.link= +platform.framework.prefix=-F +platform.framework.suffix= +platform.framework= +platform.library.prefix=lib +platform.library.suffix=.so http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.11/pom.xml ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.11/pom.xml b/viennacl-omp/scala-2.11/pom.xml index 739132e..d3dc5dc 100644 --- a/viennacl-omp/scala-2.11/pom.xml +++ b/viennacl-omp/scala-2.11/pom.xml @@ -18,16 +18,20 @@ --> <project xmlns="http://maven.apache.org/POM/4.0.0"; xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"; xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd";> - <modelVersion>4.0.0</modelVersion> - <parent> - <groupId>org.apache.mahout</groupId> - <artifactId>mahout-native-viennacl-omp</artifactId> - <version>0.13.2-SNAPSHOT</version> - <relativePath>../pom.xml</relativePath> - </parent> + <modelVersion>4.0.0</modelVersion> - <artifactId>mahout-native-viennacl-omp_2.11</artifactId> - <name>Mahout Native VienniaCL OpenCL OpenMP Bindings for Scala 2.11</name> + <parent> + <groupId>org.apache.mahout</groupId> + <artifactId>mahout</artifactId> + <version>0.13.2-SNAPSHOT</version> + <relativePath>../pom.xml</relativePath> + </parent> + + <artifactId>mahout-native-viennacl-omp_2.11</artifactId> + + <name>Mahout Native VienniaCL OpenMP Bindings</name> + <description>Native Structures and interfaces to be used from Mahout math-scala. + </description> <properties> @@ -35,33 +39,282 @@ <scala.version>2.11.8</scala.version> </properties> - <packaging>jar</packaging> + <packaging>jar</packaging> + + <build> + <plugins> + <!-- create test jar so other modules can reuse the native test utility classes. --> + <plugin> + <groupId>org.apache.maven.plugins</groupId> + <artifactId>maven-jar-plugin</artifactId> + <executions> + <execution> + <goals> + <goal>test-jar</goal> + </goals> + <phase>package</phase> + </execution> + </executions> + </plugin> + + <plugin> + <artifactId>maven-javadoc-plugin</artifactId> + </plugin> + + <plugin> + <artifactId>maven-source-plugin</artifactId> + </plugin> + + <plugin> + <groupId>net.alchim31.maven</groupId> + <artifactId>scala-maven-plugin</artifactId> + <executions> + <execution> + <id>add-scala-sources</id> + <phase>initialize</phase> + <goals> + <goal>add-source</goal> + </goals> + </execution> + <execution> + <id>scala-compile</id> + <phase>process-resources</phase> + <goals> + <goal>compile</goal> + </goals> + </execution> + <execution> + <id>scala-test-compile</id> + <phase>process-test-resources</phase> + <goals> + <goal>testCompile</goal> + </goals> + </execution> + </executions> + </plugin> + + <!--this is what scalatest recommends to do to enable scala tests --> + + <!-- disable surefire --> + <!-- disable surefire --> + <plugin> + <groupId>org.apache.maven.plugins</groupId> + <artifactId>maven-surefire-plugin</artifactId> + <configuration> + <skipTests>true</skipTests> + </configuration> + </plugin> + <!-- enable scalatest --> + <plugin> + <groupId>org.scalatest</groupId> + <artifactId>scalatest-maven-plugin</artifactId> + <executions> + <execution> + <id>test</id> + <goals> + <goal>test</goal> + </goals> + </execution> + </executions> + <configuration> + <argLine>-Xmx4g</argLine> + </configuration> + </plugin> + + + <!--JavaCPP native build plugin--> + <!-- old-style way to get it to compile. --> + <!--based on https://github.com/bytedeco/javacpp/wiki/Maven--> + <plugin> + <groupId>org.codehaus.mojo</groupId> + <artifactId>exec-maven-plugin</artifactId> + <version>1.2.1</version> + <executions> + <execution> + <id>javacpp</id> + <phase>process-classes</phase> + <goals> + <goal>exec</goal> + </goals> + <configuration> + <environmentVariables> + <LD_LIBRARY_PATH>{project.basedir}/target/classes/org/apache/mahout/javacpp/linalg/linux-x86_64/ + </LD_LIBRARY_PATH> + </environmentVariables> + <executable>java</executable> + <arguments> + <argument>-jar</argument> + <argument>${org.bytedeco:javacpp:jar}</argument> + <argument>-propertyfile</argument> + <argument>linux-x86_64-viennacl.properties</argument> + <argument>-classpath</argument> + <argument>${project.build.outputDirectory}:${org.scala-lang:scala-library:jar}</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.CompressedMatrix</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.Context</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.MatrixBase</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.DenseRowMatrix</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.DenseColumnMatrix</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.MatMatProdExpression</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.ProdExpression</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.MatrixTransExpression</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.LinalgFunctions</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.Functions</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.VectorBase</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.VCLVector</argument> + <argument>org.apache.mahout.viennacl.openmp.javacpp.VecMultExpression</argument> + <argument>org.apache.mahout.viennacl.openmp.OMPMMul</argument> + <argument>org.apache.mahout.viennacl.openmp.OMPMMul$</argument> + </arguments> + </configuration> + </execution> + </executions> + </plugin> + + <plugin> + <groupId>org.apache.maven.plugins</groupId> + <artifactId>maven-dependency-plugin</artifactId> + <version>2.3</version> + <executions> + <execution> + <goals> + <goal>properties</goal> + </goals> + </execution> + </executions> + </plugin> + <plugin> + <groupId>org.codehaus.mojo</groupId> + <artifactId>exec-maven-plugin</artifactId> + <version>1.2.1</version> + </plugin> + + <!-- copy jars to top directory, which is MAHOUT_HOME --> + <plugin> + <artifactId>maven-antrun-plugin</artifactId> + <version>1.4</version> + <executions> + <execution> + <id>copy</id> + <phase>package</phase> + <configuration> + <tasks> + <copy file="target/mahout-native-viennacl-omp_2.11-${project.version}.jar" tofile="../../mahout-native-viennacl-omp_2.11-${project.version}.jar" /> + </tasks> + </configuration> + <goals> + <goal>run</goal> + </goals> + </execution> + </executions> + </plugin> + <!-- delete jars on claen in top directory, which is MAHOUT_HOME --> + <plugin> + <artifactId>maven-clean-plugin</artifactId> + <version>3.0.0</version> + <configuration> + <filesets> + <fileset> + <directory>../../</directory> + <includes> + <include>mahout-native-viennacl-omp_2.11*.jar</include> + </includes> + <followSymlinks>false</followSymlinks> + </fileset> + </filesets> + </configuration> + </plugin> + </plugins> - <build> - <sourceDirectory>../src/main</sourceDirectory> - <plugins> - <plugin> - <artifactId>maven-antrun-plugin</artifactId> - <executions> - <execution> - <id>copy</id> - <phase>package</phase> - </execution> - </executions> - </plugin> - <!-- disable javacpp recompile, its wasteful and causes issues --> - <plugin> - <groupId>org.codehaus.mojo</groupId> - <artifactId>exec-maven-plugin</artifactId> - <executions> - <execution> - <id>javacpp</id> - <phase/> - </execution> - </executions> - </plugin> - </plugins> - </build> -</project> \ No newline at end of file + </build> + + <dependencies> + + <dependency> + <groupId>${project.groupId}</groupId> + <artifactId>mahout-math-scala_${scala.compat.version}</artifactId> + </dependency> + + <!-- 3rd-party --> + <dependency> + <groupId>log4j</groupId> + <artifactId>log4j</artifactId> + </dependency> + + <!-- scala stuff --> + <dependency> + <groupId>org.scalatest</groupId> + <artifactId>scalatest_${scala.compat.version}</artifactId> + </dependency> + + <!-- scala-library for annotations at compile time--> + <!--<dependency>--> + <!--<groupId>org.scala-lang</groupId>--> + <!--<artifactId>scala-library</artifactId>--> + <!--<version>${scala.version}</version>--> + <!--</dependency>--> + + + <dependency> + <groupId>org.bytedeco</groupId> + <artifactId>javacpp</artifactId> + <version>1.2.4</version> + </dependency> + + </dependencies> + + + <profiles> + <profile> + <id>mahout-release</id> + <build> + <plugins> + <plugin> + <groupId>net.alchim31.maven</groupId> + <artifactId>scala-maven-plugin</artifactId> + <executions> + <execution> + <id>generate-scaladoc</id> + <goals> + <goal>doc</goal> + </goals> + </execution> + <execution> + <id>attach-scaladoc-jar</id> + <goals> + <goal>doc-jar</goal> + </goals> + </execution> + </executions> + </plugin> + </plugins> + </build> + </profile> + <profile> + <id>travis</id> + <build> + <plugins> + <plugin> + <groupId>org.apache.maven.plugins</groupId> + <artifactId>maven-surefire-plugin</artifactId> + <configuration> + <!-- Limit memory for unit tests in Travis --> + <argLine>-Xmx3g</argLine> + <!--<argLine>-Djava.library.path=${project.build.directory}/libs/natives/linux-x86_64:${project.build.directory}/libs/natives/linux:${project.build.directory}/libs/natives/maxosx</argLine>--> + </configuration> + </plugin> + <plugin> + <groupId>org.apache.maven.plugins</groupId> + <artifactId>maven-failsafe-plugin</artifactId> + <configuration> + <!-- Limit memory for integration tests in Travis --> + <argLine>-Xmx3g</argLine> + <!--<argLine>-Djava.library.path=${project.build.directory}/libs/natives/linux-x86_64:${project.build.directory}/libs/natives/linux:${project.build.directory}/libs/natives/maxosx</argLine>--> + </configuration> + </plugin> + </plugins> + </build> + </profile> + </profiles> +</project> http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.11/runs ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.11/runs b/viennacl-omp/scala-2.11/runs new file mode 100644 index 0000000..a152244 --- /dev/null +++ b/viennacl-omp/scala-2.11/runs @@ -0,0 +1,32 @@ +original +row-major viennacl::matrix + + OCL matrix memory domain after assgn=2 +- dense vcl mmul with fast_copy +- mmul microbenchmark + + Mahout multiplication time: 15699 ms. + + ViennaCL/OpenCL multiplication time: 3625 ms. + + ompA mem domain:1 + + ompB mem domain:1 + + ViennaCL/cpu/OpenMP multiplication time: 2838 ms. + +with sys.ArrayCopy, all dense. +ViennaCLSuite: +- row-major viennacl::matrix + + OCL matrix memory domain after assgn=2 +- dense vcl mmul with fast_copy +- mmul microbenchmark + + Mahout multiplication time: 15407 ms. + + ViennaCL/OpenCL multiplication time: 3499 ms. + + ompA mem domain:1 + + ompB mem domain:1 + + ViennaCL/cpu/OpenMP multiplication time: 2714 ms. + +DL latest +ViennaCLSuite: +- row-major viennacl::matrix + + OCL matrix memory domain after assgn=2 +- dense vcl mmul with fast_copy +- mmul microbenchmark + + Mahout multiplication time: 16076 ms. + + ViennaCL/OpenCL multiplication time: 3360 ms. + + ViennaCL/cpu/OpenMP multiplication time: 2666 ms. http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.11/src/main/java/org/apache/mahout/viennacl/openmp/javacpp/Functions.java ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.11/src/main/java/org/apache/mahout/viennacl/openmp/javacpp/Functions.java b/viennacl-omp/scala-2.11/src/main/java/org/apache/mahout/viennacl/openmp/javacpp/Functions.java new file mode 100644 index 0000000..c2bffe5 --- /dev/null +++ b/viennacl-omp/scala-2.11/src/main/java/org/apache/mahout/viennacl/openmp/javacpp/Functions.java @@ -0,0 +1,103 @@ +/** + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.mahout.viennacl.openmp.javacpp; + +import org.bytedeco.javacpp.BytePointer; +import org.bytedeco.javacpp.DoublePointer; +import org.bytedeco.javacpp.IntPointer; +import org.bytedeco.javacpp.annotation.*; + +import java.nio.DoubleBuffer; +import java.nio.IntBuffer; + + +@Properties(inherit = Context.class, + value = @Platform( + library = "jniViennaCL" + ) +) +@Namespace("viennacl") +public final class Functions { + + private Functions() { + } + + // This is (imo) an inconsistency in Vienna cl: almost all operations require MatrixBase, and + // fast_copy require type `matrix`, i.e., one of DenseRowMatrix or DenseColumnMatrix. + @Name("fast_copy") + public static native void fastCopy(DoublePointer srcBegin, DoublePointer srcEnd, @ByRef DenseRowMatrix dst); + + @Name("fast_copy") + public static native void fastCopy(DoublePointer srcBegin, DoublePointer srcEnd, @ByRef DenseColumnMatrix dst); + + @Name("fast_copy") + public static native void fastCopy(@ByRef DenseRowMatrix src, DoublePointer dst); + + @Name("fast_copy") + public static native void fastCopy(@ByRef DenseColumnMatrix src, DoublePointer dst); + + @Name("fast_copy") + public static native void fastCopy(@Const @ByRef VectorBase dst, @Const @ByRef VCLVector src); + + @Name("fast_copy") + public static native void fastCopy(@Const @ByRef VCLVector src, @Const @ByRef VectorBase dst); + + + @ByVal + public static native MatrixTransExpression trans(@ByRef MatrixBase src); + + @Name("backend::memory_read") + public static native void memoryReadInt(@Const @ByRef MemHandle src_buffer, + int bytes_to_read, + int offset, + IntPointer ptr, + boolean async); + + @Name("backend::memory_read") + public static native void memoryReadDouble(@Const @ByRef MemHandle src_buffer, + int bytes_to_read, + int offset, + DoublePointer ptr, + boolean async); + + @Name("backend::memory_read") + public static native void memoryReadInt(@Const @ByRef MemHandle src_buffer, + int bytes_to_read, + int offset, + IntBuffer ptr, + boolean async); + + @Name("backend::memory_read") + public static native void memoryReadDouble(@Const @ByRef MemHandle src_buffer, + int bytes_to_read, + int offset, + DoubleBuffer ptr, + boolean async); + + @Name("backend::memory_read") + public static native void memoryReadBytes(@Const @ByRef MemHandle src_buffer, + int bytes_to_read, + int offset, + BytePointer ptr, + boolean async); + + + static { + Context.loadLib(); + } + +} http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.11/src/main/java/org/apache/mahout/viennacl/openmp/javacpp/LinalgFunctions.java ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.11/src/main/java/org/apache/mahout/viennacl/openmp/javacpp/LinalgFunctions.java b/viennacl-omp/scala-2.11/src/main/java/org/apache/mahout/viennacl/openmp/javacpp/LinalgFunctions.java new file mode 100644 index 0000000..c2a40d9 --- /dev/null +++ b/viennacl-omp/scala-2.11/src/main/java/org/apache/mahout/viennacl/openmp/javacpp/LinalgFunctions.java @@ -0,0 +1,86 @@ +/** + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.mahout.viennacl.openmp.javacpp; + +import org.apache.mahout.viennacl.openmp.javacpp.*; +import org.bytedeco.javacpp.annotation.*; + + +@Properties(inherit = Context.class, + value = @Platform( + library = "jniViennaCL" + ) +) +@Namespace("viennacl::linalg") +public final class LinalgFunctions { + + private LinalgFunctions() { + } + + static { + Context.loadLib(); + } + + + @ByVal + public static native MatMatProdExpression prod(@Const @ByRef MatrixBase a, + @Const @ByRef MatrixBase b); + + @ByVal + public static native ProdExpression prod(@Const @ByRef CompressedMatrix a, + @Const @ByRef CompressedMatrix b); + + @ByVal + public static native MatVecProdExpression prod(@Const @ByRef MatrixBase a, + @Const @ByRef VectorBase b); + + @ByVal + public static native SrMatDnMatProdExpression prod(@Const @ByRef CompressedMatrix spMx, + @Const @ByRef MatrixBase dMx); + @ByVal + @Name("prod") + public static native DenseColumnMatrix prodCm(@Const @ByRef MatrixBase a, + @Const @ByRef MatrixBase b); + @ByVal + @Name("prod") + public static native DenseRowMatrix prodRm(@Const @ByRef MatrixBase a, + @Const @ByRef MatrixBase b); + + @ByVal + @Name("prod") + public static native DenseRowMatrix prodRm(@Const @ByRef CompressedMatrix spMx, + @Const @ByRef MatrixBase dMx); + + +// @ByVal +// public static native MatrixProdExpression prod(@Const @ByRef DenseRowMatrix a, +// @Const @ByRef DenseRowMatrix b); +// +// @ByVal +// public static native MatrixProdExpression prod(@Const @ByRef DenseRowMatrix a, +// @Const @ByRef DenseColumnMatrix b); +// +// @ByVal +// public static native MatrixProdExpression prod(@Const @ByRef DenseColumnMatrix a, +// @Const @ByRef DenseRowMatrix b); +// +// @ByVal +// public static native MatrixProdExpression prod(@Const @ByRef DenseColumnMatrix a, +// @Const @ByRef DenseColumnMatrix b); + + +} http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.11/src/main/java/org/apache/mahout/viennacl/openmp/javacpp/MatrixTransExpression.scala ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.11/src/main/java/org/apache/mahout/viennacl/openmp/javacpp/MatrixTransExpression.scala b/viennacl-omp/scala-2.11/src/main/java/org/apache/mahout/viennacl/openmp/javacpp/MatrixTransExpression.scala new file mode 100644 index 0000000..82574b4 --- /dev/null +++ b/viennacl-omp/scala-2.11/src/main/java/org/apache/mahout/viennacl/openmp/javacpp/MatrixTransExpression.scala @@ -0,0 +1,34 @@ +/** + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ +package org.apache.mahout.viennacl.openmp.javacpp; + +import org.bytedeco.javacpp.Pointer +import org.bytedeco.javacpp.annotation.{Name, Namespace, Platform, Properties} + + +@Properties(inherit = Array(classOf[Context]), + value = Array(new Platform( + include = Array("matrix.hpp"), + library = "jniViennaCL") + )) +@Namespace("viennacl") +@Name(Array("matrix_expression<const viennacl::matrix_base<double>, " + + "const viennacl::matrix_base<double>, " + + "viennacl::op_trans>")) +class MatrixTransExpression extends Pointer { + +} http://git-wip-us.apache.org/repos/asf/mahout/blob/9a4f9d36/viennacl-omp/scala-2.11/src/main/scala/org/apache/mahout/viennacl/openmp/OMPMMul.scala ---------------------------------------------------------------------- diff --git a/viennacl-omp/scala-2.11/src/main/scala/org/apache/mahout/viennacl/openmp/OMPMMul.scala b/viennacl-omp/scala-2.11/src/main/scala/org/apache/mahout/viennacl/openmp/OMPMMul.scala new file mode 100644 index 0000000..9a59999 --- /dev/null +++ b/viennacl-omp/scala-2.11/src/main/scala/org/apache/mahout/viennacl/openmp/OMPMMul.scala @@ -0,0 +1,449 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.mahout.viennacl.openmp + +import org.apache.mahout.logging._ +import org.apache.mahout.math +import org.apache.mahout.math._ +import org.apache.mahout.math.backend.incore.MMulSolver +import org.apache.mahout.math.flavor.{BackEnum, TraversingStructureEnum} +import org.apache.mahout.math.function.Functions +import org.apache.mahout.math.scalabindings.RLikeOps._ +import org.apache.mahout.math.scalabindings._ +import org.apache.mahout.viennacl.openmp.javacpp.Functions._ +import org.apache.mahout.viennacl.openmp.javacpp.LinalgFunctions._ +import org.apache.mahout.viennacl.openmp.javacpp.{CompressedMatrix, Context, DenseRowMatrix} + +import scala.collection.JavaConversions._ + +object OMPMMul extends MMBinaryFunc { + + private implicit val log = getLog(OMPMMul.getClass) + + override def apply(a: Matrix, b: Matrix, r: Option[Matrix]): Matrix = { + + require(a.ncol == b.nrow, "Incompatible matrix sizes in matrix multiplication.") + + val (af, bf) = (a.getFlavor, b.getFlavor) + val backs = (af.getBacking, bf.getBacking) + val sd = (af.getStructure, math.scalabindings.densityAnalysis(a), bf.getStructure, densityAnalysis(b)) + + + try { + + val alg: MMulAlg = backs match { + + // Both operands are jvm memory backs. + case (BackEnum.JVMMEM, BackEnum.JVMMEM) â + + sd match { + + // Multiplication cases by a diagonal matrix. + case (TraversingStructureEnum.VECTORBACKED, _, TraversingStructureEnum.COLWISE, _) + if a.isInstanceOf[DiagonalMatrix] â jvmDiagCW + case (TraversingStructureEnum.VECTORBACKED, _, TraversingStructureEnum.SPARSECOLWISE, _) + if a.isInstanceOf[DiagonalMatrix] â jvmDiagCW + case (TraversingStructureEnum.VECTORBACKED, _, TraversingStructureEnum.ROWWISE, _) + if a.isInstanceOf[DiagonalMatrix] â jvmDiagRW + case (TraversingStructureEnum.VECTORBACKED, _, TraversingStructureEnum.SPARSEROWWISE, _) + if a.isInstanceOf[DiagonalMatrix] â jvmDiagRW + + case (TraversingStructureEnum.COLWISE, _, TraversingStructureEnum.VECTORBACKED, _) + if b.isInstanceOf[DiagonalMatrix] â jvmCWDiag + case (TraversingStructureEnum.SPARSECOLWISE, _, TraversingStructureEnum.VECTORBACKED, _) + if b.isInstanceOf[DiagonalMatrix] â jvmCWDiag + case (TraversingStructureEnum.ROWWISE, _, TraversingStructureEnum.VECTORBACKED, _) + if b.isInstanceOf[DiagonalMatrix] â jvmRWDiag + case (TraversingStructureEnum.SPARSEROWWISE, _, TraversingStructureEnum.VECTORBACKED, _) + if b.isInstanceOf[DiagonalMatrix] â jvmRWDiag + + // Dense-dense cases + case (TraversingStructureEnum.ROWWISE, true, TraversingStructureEnum.COLWISE, true) if a eq b.t â ompDRWAAt + case (TraversingStructureEnum.ROWWISE, true, TraversingStructureEnum.COLWISE, true) if a.t eq b â ompDRWAAt + case (TraversingStructureEnum.ROWWISE, true, TraversingStructureEnum.COLWISE, true) â ompRWCW + case (TraversingStructureEnum.ROWWISE, true, TraversingStructureEnum.ROWWISE, true) â jvmRWRW + case (TraversingStructureEnum.COLWISE, true, TraversingStructureEnum.COLWISE, true) â jvmCWCW + case (TraversingStructureEnum.COLWISE, true, TraversingStructureEnum.ROWWISE, true) if a eq b.t â jvmDCWAAt + case (TraversingStructureEnum.COLWISE, true, TraversingStructureEnum.ROWWISE, true) if a.t eq b â jvmDCWAAt + case (TraversingStructureEnum.COLWISE, true, TraversingStructureEnum.ROWWISE, true) â jvmCWRW + + // Sparse row matrix x sparse row matrix (array of vectors) + case (TraversingStructureEnum.ROWWISE, false, TraversingStructureEnum.ROWWISE, false) â ompSparseRWRW + case (TraversingStructureEnum.ROWWISE, false, TraversingStructureEnum.COLWISE, false) â jvmSparseRWCW + case (TraversingStructureEnum.COLWISE, false, TraversingStructureEnum.ROWWISE, false) â jvmSparseCWRW + case (TraversingStructureEnum.COLWISE, false, TraversingStructureEnum.COLWISE, false) â jvmSparseCWCW + + // Sparse matrix x sparse matrix (hashtable of vectors) + case (TraversingStructureEnum.SPARSEROWWISE, false, TraversingStructureEnum.SPARSEROWWISE, false) â + ompSparseRowRWRW + case (TraversingStructureEnum.SPARSEROWWISE, false, TraversingStructureEnum.SPARSECOLWISE, false) â + jvmSparseRowRWCW + case (TraversingStructureEnum.SPARSECOLWISE, false, TraversingStructureEnum.SPARSEROWWISE, false) â + jvmSparseRowCWRW + case (TraversingStructureEnum.SPARSECOLWISE, false, TraversingStructureEnum.SPARSECOLWISE, false) â + jvmSparseRowCWCW + + // Sparse matrix x non-like + case (TraversingStructureEnum.SPARSEROWWISE, false, TraversingStructureEnum.ROWWISE, _) â ompSparseRowRWRW + case (TraversingStructureEnum.SPARSEROWWISE, false, TraversingStructureEnum.COLWISE, _) â jvmSparseRowRWCW + case (TraversingStructureEnum.SPARSECOLWISE, false, TraversingStructureEnum.ROWWISE, _) â jvmSparseRowCWRW + case (TraversingStructureEnum.SPARSECOLWISE, false, TraversingStructureEnum.COLWISE, _) â jvmSparseCWCW + case (TraversingStructureEnum.ROWWISE, _, TraversingStructureEnum.SPARSEROWWISE, false) â ompSparseRWRW + case (TraversingStructureEnum.ROWWISE, _, TraversingStructureEnum.SPARSECOLWISE, false) â jvmSparseRWCW + case (TraversingStructureEnum.COLWISE, _, TraversingStructureEnum.SPARSEROWWISE, false) â jvmSparseCWRW + case (TraversingStructureEnum.COLWISE, _, TraversingStructureEnum.SPARSECOLWISE, false) â jvmSparseRowCWCW + + // Everything else including at least one sparse LHS or RHS argument + case (TraversingStructureEnum.ROWWISE, false, TraversingStructureEnum.ROWWISE, _) â ompSparseRWRW + case (TraversingStructureEnum.ROWWISE, false, TraversingStructureEnum.COLWISE, _) â jvmSparseRWCW + case (TraversingStructureEnum.COLWISE, false, TraversingStructureEnum.ROWWISE, _) â jvmSparseCWRW + case (TraversingStructureEnum.COLWISE, false, TraversingStructureEnum.COLWISE, _) â jvmSparseCWCW2flips + + // Sparse methods are only effective if the first argument is sparse, so we need to do a swap. + case (_, _, _, false) â (a, b, r) â apply(b.t, a.t, r.map { + _.t + }).t + + // Default jvm-jvm case. + // for some reason a SrarseRowMatrix DRM %*% SrarseRowMatrix DRM was dumping off to here + case _ â ompRWCW + } + } + + alg(a, b, r) + } catch { + // TODO FASTHACK: just revert to JVM if there is an exception.. + // eg. java.lang.nullPointerException if more openCL contexts + // have been created than number of GPU cards. + // better option wuold be to fall back to OpenCl First. + case ex: Exception => + println(ex.getMessage + "falling back to JVM MMUL") + return MMul(a, b, r) + } + } + + type MMulAlg = MMBinaryFunc + + @inline + private def ompRWCW(a: Matrix, b: Matrix, r: Option[Matrix] = None): Matrix = { + println("ompRWCW") + // + // require(r.forall(mxR â mxR.nrow == a.nrow && mxR.ncol == b.ncol)) + // val (m, n) = (a.nrow, b.ncol) + // + // val mxR = r.getOrElse(if (densityAnalysis(a)) a.like(m, n) else b.like(m, n)) + // + // for (row â 0 until mxR.nrow; col â 0 until mxR.ncol) { + // // this vector-vector should be sort of optimized, right? + // mxR(row, col) = a(row, ::) dot b(::, col) + // } + // mxR + + val hasElementsA = a.zSum() > 0.0 + val hasElementsB = b.zSum() > 0.0 + + // A has a sparse matrix structure of unknown size. We do not want to + // simply convert it to a Dense Matrix which may result in an OOM error. + + // If it is empty use JVM MMul, since we can not convert it to a VCL CSR Matrix. + if (!hasElementsA) { + println("Matrix a has zero elements can not convert to CSR") + return MMul(a, b, r) + } + + // CSR matrices are efficient up to 50% non-zero + if (b.getFlavor.isDense) { + var ms = System.currentTimeMillis() + val oclCtx = new Context(Context.MAIN_MEMORY) + val oclA = toVclCmpMatrixAlt(a, oclCtx) + val oclB = toVclDenseRM(b, oclCtx) + val oclC = new DenseRowMatrix(prod(oclA, oclB)) + val mxC = fromVclDenseRM(oclC) + ms = System.currentTimeMillis() - ms + debug(s"ViennaCL/OpenMP multiplication time: $ms ms.") + + oclA.close() + oclB.close() + oclC.close() + + mxC + } else { + // Fall back to JVM based MMul if either matrix is sparse and empty + if (!hasElementsA || !hasElementsB) { + println("Matrix a or b has zero elements can not convert to CSR") + return MMul(a, b, r) + } + + var ms = System.currentTimeMillis() + val hostClCtx = new Context(Context.MAIN_MEMORY) + val oclA = toVclCmpMatrixAlt(a, hostClCtx) + val oclB = toVclCmpMatrixAlt(b, hostClCtx) + val oclC = new CompressedMatrix(prod(oclA, oclB)) + val mxC = fromVclCompressedMatrix(oclC) + ms = System.currentTimeMillis() - ms + debug(s"ViennaCL/OpenMP multiplication time: $ms ms.") + + oclA.close() + oclB.close() + oclC.close() + + mxC + } + } + + + @inline + private def jvmRWRW(a: Matrix, b: Matrix, r: Option[Matrix] = None): Matrix = { + log.info("Using jvmRWRW method") + // A bit hackish: currently, this relies a bit on the fact that like produces RW(?) + val bclone = b.like(b.ncol, b.nrow).t + for (brow â b) bclone(brow.index(), ::) := brow + + require(bclone.getFlavor.getStructure == TraversingStructureEnum.COLWISE || bclone.getFlavor.getStructure == + TraversingStructureEnum.SPARSECOLWISE, "COL wise conversion assumption of RHS is wrong, do over this code.") + + ompRWCW(a, bclone, r) + } + + private def jvmCWCW(a: Matrix, b: Matrix, r: Option[Matrix] = None): Matrix = { + log.info("Using jvmCWCW method") + jvmRWRW(b.t, a.t, r.map(_.t)).t + } + + private def jvmCWRW(a: Matrix, b: Matrix, r: Option[Matrix] = None): Matrix = { + log.info("Using jvmCWRW method") + // This is a primary contender with Outer Prod sum algo. + // Here, we force-reorient both matrices and run RWCW. + // A bit hackish: currently, this relies a bit on the fact that clone always produces RW(?) + val aclone = a.cloned + + require(aclone.getFlavor.getStructure == TraversingStructureEnum.ROWWISE || aclone.getFlavor.getStructure == + TraversingStructureEnum.SPARSEROWWISE, "Row wise conversion assumption of RHS is wrong, do over this code.") + + jvmRWRW(aclone, b, r) + } + + // left is Sparse right is any + private def ompSparseRWRW(a: Matrix, b: Matrix, r: Option[Matrix] = None): Matrix = { + log.info("Using ompSparseRWRW method") + val mxR = r.getOrElse(b.like(a.nrow, b.ncol)) + + /* Make sure that the matrix is not empty. VCL {{compressed_matrix}}s must + have nnz > 0 + N.B. This method is horribly inefficent. However there is a difference between + getNumNonDefaultElements() and getNumNonZeroElements() which we do not always + have access to. We created MAHOUT-1882 for this. + */ + + val hasElementsA = a.zSum() > 0.0 + val hasElementsB = b.zSum() > 0.0 + + // A has a sparse matrix structure of unknown size. We do not want to + // simply convert it to a Dense Matrix which may result in an OOM error. + // If it is empty use JVM MMul, since we can not convert it to a VCL CSR Matrix. + if (!hasElementsA) { + log.warn("Matrix a has zero elements can not convert to CSR") + return MMul(a, b, r) + } + + // CSR matrices are efficient up to 50% non-zero + if(b.getFlavor.isDense) { + var ms = System.currentTimeMillis() + val hostClCtx = new Context(Context.MAIN_MEMORY) + val oclA = toVclCmpMatrixAlt(a, hostClCtx) + val oclB = toVclDenseRM(b, hostClCtx) + val oclC = new DenseRowMatrix(prod(oclA, oclB)) + val mxC = fromVclDenseRM(oclC) + ms = System.currentTimeMillis() - ms + log.debug(s"ViennaCL/OpenMP multiplication time: $ms ms.") + + oclA.close() + oclB.close() + oclC.close() + + mxC + } else { + // Fall back to JVM based MMul if either matrix is sparse and empty + if (!hasElementsA || !hasElementsB) { + log.warn("Matrix a or b has zero elements can not convert to CSR") + return MMul(a, b, r) + } + + var ms = System.currentTimeMillis() + val hostClCtx = new Context(Context.MAIN_MEMORY) + val oclA = toVclCmpMatrixAlt(a, hostClCtx) + val oclB = toVclCmpMatrixAlt(b, hostClCtx) + val oclC = new CompressedMatrix(prod(oclA, oclB)) + val mxC = fromVclCompressedMatrix(oclC) + ms = System.currentTimeMillis() - ms + log.debug(s"ViennaCL/OpenMP multiplication time: $ms ms.") + + oclA.close() + oclB.close() + oclC.close() + + mxC + } + + } + + //sparse %*% dense + private def ompSparseRowRWRW(a: Matrix, b: Matrix, r: Option[Matrix] = None): Matrix = { + log.info("Using ompSparseRowRWRW method") + val hasElementsA = a.zSum() > 0 + + // A has a sparse matrix structure of unknown size. We do not want to + // simply convert it to a Dense Matrix which may result in an OOM error. + // If it is empty fall back to JVM MMul, since we can not convert it + // to a VCL CSR Matrix. + if (!hasElementsA) { + log.warn("Matrix a has zero elements can not convert to CSR") + return MMul(a, b, r) + } + + var ms = System.currentTimeMillis() + val hostClCtx = new Context(Context.MAIN_MEMORY) + val oclA = toVclCmpMatrixAlt(a, hostClCtx) + val oclB = toVclDenseRM(b, hostClCtx) + val oclC = new DenseRowMatrix(prod(oclA, oclB)) + val mxC = fromVclDenseRM(oclC) + ms = System.currentTimeMillis() - ms + log.debug(s"ViennaCL/OpenMP multiplication time: $ms ms.") + + oclA.close() + oclB.close() + oclC.close() + + mxC + } + + private def jvmSparseRowCWCW(a: Matrix, b: Matrix, r: Option[Matrix] = None) = + ompSparseRowRWRW(b.t, a.t, r.map(_.t)).t + + private def jvmSparseRowCWCW2flips(a: Matrix, b: Matrix, r: Option[Matrix] = None) = + ompSparseRowRWRW(a cloned, b cloned, r) + + private def jvmSparseRowRWCW(a: Matrix, b: Matrix, r: Option[Matrix]) = + ompSparseRowRWRW(a, b cloned, r) + + private def jvmSparseRowCWRW(a: Matrix, b: Matrix, r: Option[Matrix]) = + ompSparseRowRWRW(a cloned, b, r) + + private def jvmSparseRWCW(a: Matrix, b: Matrix, r: Option[Matrix] = None) = + ompSparseRWRW(a, b.cloned, r) + + private def jvmSparseCWRW(a: Matrix, b: Matrix, r: Option[Matrix] = None) = + ompSparseRWRW(a cloned, b, r) + + private def jvmSparseCWCW(a: Matrix, b: Matrix, r: Option[Matrix] = None) = + ompSparseRWRW(b.t, a.t, r.map(_.t)).t + + private def jvmSparseCWCW2flips(a: Matrix, b: Matrix, r: Option[Matrix] = None) = + ompSparseRWRW(a cloned, b cloned, r) + + private def jvmDiagRW(diagm:Matrix, b:Matrix, r:Option[Matrix] = None):Matrix = { + log.info("Using jvmDiagRW method") + val mxR = r.getOrElse(b.like(diagm.nrow, b.ncol)) + + for (del â diagm.diagv.nonZeroes()) + mxR(del.index, ::).assign(b(del.index, ::), Functions.plusMult(del)) + + mxR + } + + private def jvmDiagCW(diagm: Matrix, b: Matrix, r: Option[Matrix] = None): Matrix = { + log.info("Using jvmDiagCW method") + val mxR = r.getOrElse(b.like(diagm.nrow, b.ncol)) + for (bcol â b.t) mxR(::, bcol.index()) := bcol * diagm.diagv + mxR + } + + private def jvmCWDiag(a: Matrix, diagm: Matrix, r: Option[Matrix] = None) = + jvmDiagRW(diagm, a.t, r.map {_.t}).t + + private def jvmRWDiag(a: Matrix, diagm: Matrix, r: Option[Matrix] = None) = + jvmDiagCW(diagm, a.t, r.map {_.t}).t + + /** Dense column-wise AA' */ + private def jvmDCWAAt(a:Matrix, b:Matrix, r:Option[Matrix] = None) = { + // a.t must be equiv. to b. Cloning must rewrite to row-wise. + ompDRWAAt(a.cloned,null,r) + } + + /** Dense Row-wise AA' */ + // We probably will not want to use this for the actual release unless A is cached already + // but adding for testing purposes. + private def ompDRWAAt(a:Matrix, b:Matrix, r:Option[Matrix] = None) = { + // a.t must be equiv to b. + log.info("Executing on OMP") + log.debug("AAt computation detected; passing off to OMP") + + // Check dimensions if result is supplied. + require(r.forall(mxR â mxR.nrow == a.nrow && mxR.ncol == a.nrow)) + + val mxR = r.getOrElse(a.like(a.nrow, a.nrow)) + + var ms = System.currentTimeMillis() + val hostClCtx = new Context(Context.MAIN_MEMORY) + val oclA = toVclDenseRM(src = a, hostClCtx) + val oclAt = new DenseRowMatrix(trans(oclA)) + val oclC = new DenseRowMatrix(prod(oclA, oclAt)) + + val mxC = fromVclDenseRM(oclC) + ms = System.currentTimeMillis() - ms + log.debug(s"ViennaCL/OpenMP multiplication time: $ms ms.") + + oclA.close() + //oclApr.close() + oclAt.close() + oclC.close() + + mxC + + } + + private def jvmOuterProdSum(a: Matrix, b: Matrix, r: Option[Matrix] = None): Matrix = { + log.info("Using jvmOuterProdSum method") + // Need to check whether this is already laid out for outer product computation, which may be faster than + // reorienting both matrices. + val (m, n) = (a.nrow, b.ncol) + + // Prefer col-wise result iff a is dense and b is sparse. In all other cases default to row-wise. + val preferColWiseR = a.getFlavor.isDense && !b.getFlavor.isDense + + val mxR = r.getOrElse { + (a.getFlavor.isDense, preferColWiseR) match { + case (false, false) â b.like(m, n) + case (false, true) â b.like(n, m).t + case (true, false) â a.like(m, n) + case (true, true) â a.like(n, m).t + } + } + + // Loop outer products + if (preferColWiseR) { + // this means B is sparse and A is not, so we need to iterate over b values and update R columns with += + // one at a time. + for ((acol, brow) â a.t.zip(b); bel â brow.nonZeroes) mxR(::, bel.index()) += bel * acol + } else { + for ((acol, brow) â a.t.zip(b); ael â acol.nonZeroes()) mxR(ael.index(), ::) += ael * brow + } + + mxR + } +}
