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Added: incubator/singa/site/trunk/docs/software_stack.html URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/docs/software_stack.html?rev=1857927&view=auto ============================================================================== --- incubator/singa/site/trunk/docs/software_stack.html (added) +++ incubator/singa/site/trunk/docs/software_stack.html Sun Apr 21 22:05:49 2019 @@ -0,0 +1,406 @@ + + + +<!DOCTYPE html> +<!--[if IE 8]><html class="no-js lt-ie9" lang="en" > <![endif]--> +<!--[if gt IE 8]><!--> <html class="no-js" lang="en" > <!--<![endif]--> +<head> + <meta charset="utf-8"> + + <meta name="viewport" content="width=device-width, initial-scale=1.0"> + + <title>Software Stack — incubator-singa 2.0.0 documentation</title> + + + + + + + + + <script type="text/javascript" src="../_static/js/modernizr.min.js"></script> + + + <script type="text/javascript" id="documentation_options" data-url_root="../" src="../_static/documentation_options.js"></script> + <script 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class="reference internal" href="net.html">FeedForward Net</a></li> +<li class="toctree-l2"><a class="reference internal" href="initializer.html">Initializer</a></li> +<li class="toctree-l2"><a class="reference internal" href="loss.html">Loss</a></li> +<li class="toctree-l2"><a class="reference internal" href="metric.html">Metric</a></li> +<li class="toctree-l2"><a class="reference internal" href="optimizer.html">Optimizer</a></li> +<li class="toctree-l2"><a class="reference internal" href="autograd.html">Autograd in Singa</a></li> +<li class="toctree-l2"><a class="reference internal" href="data.html">Data</a></li> +<li class="toctree-l2"><a class="reference internal" href="image_tool.html">Image Tool</a></li> +<li class="toctree-l2"><a class="reference internal" href="snapshot.html">Snapshot</a></li> +<li class="toctree-l2"><a class="reference internal" href="converter.html">Caffe Converter</a></li> +<li class="toctree-l2"><a class="reference internal" href="utils.html">Utils</a></li> +<li class="toctree-l2"><a class="reference internal" href="model_zoo/index.html">Model Zoo</a></li> +<li class="toctree-l2"><a class="reference internal" href="security.html">Security</a></li> +</ul> +</li> +<li class="toctree-l1"><a class="reference internal" href="../downloads.html">Download SINGA</a></li> +</ul> +<p class="caption"><span class="caption-text">Development</span></p> +<ul> +<li class="toctree-l1"><a class="reference internal" href="../develop/schedule.html">Development Schedule</a></li> +<li class="toctree-l1"><a class="reference internal" href="../develop/how-contribute.html">How to Contribute to SINGA</a></li> +<li class="toctree-l1"><a class="reference internal" href="../develop/how-contribute.html#how-to-become-a-singa-committer">How to become a SINGA committer</a></li> +<li class="toctree-l1"><a class="reference internal" href="../develop/contribute-code.html">How to Contribute Code</a></li> +<li class="toctree-l1"><a class="reference internal" href="../develop/contribute-docs.html">How to Contribute to Documentation</a></li> +<li class="toctree-l1"><a class="reference internal" href="../develop/how-to-release.html">How to prepare a release</a></li> +</ul> +<p class="caption"><span class="caption-text">Community</span></p> +<ul> +<li class="toctree-l1"><a class="reference internal" href="../community/source-repository.html">Source Repository</a></li> +<li class="toctree-l1"><a class="reference internal" href="../community/mail-lists.html">Project Mailing Lists</a></li> +<li class="toctree-l1"><a class="reference internal" href="../community/issue-tracking.html">Issue Tracking</a></li> +<li class="toctree-l1"><a class="reference internal" href="../community/team-list.html">The SINGA Team</a></li> +</ul> + + + + </div> + </div> + </nav> + + <section data-toggle="wy-nav-shift" class="wy-nav-content-wrap"> + + + <nav class="wy-nav-top" aria-label="top navigation"> + + <i data-toggle="wy-nav-top" class="fa fa-bars"></i> + <a href="../index.html">incubator-singa</a> + + </nav> + + + <div class="wy-nav-content"> + + <div class="rst-content"> + + + + + + + + + + + + + + + + + +<div role="navigation" aria-label="breadcrumbs navigation"> + + <ul class="wy-breadcrumbs"> + + <li><a href="../index.html">Docs</a> »</li> + + <li><a href="index.html">Documentation</a> »</li> + + <li>Software Stack</li> + + + <li class="wy-breadcrumbs-aside"> + + + + </li> + + </ul> + + + <hr/> +</div> + <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article";> + <div itemprop="articleBody"> + + <!-- + 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. +--><div class="section" id="software-stack"> +<h1>Software Stack<a class="headerlink" href="#software-stack" title="Permalink to this headline">¶</a></h1> +<p>SINGAâs software stack includes three major components, namely, core, IO and +model. Figure 1 illustrates these components together with the hardware. +The core component provides memory management and tensor operations; +IO has classes for reading (and writing) data from (to) disk and network; The +model component provides data structures and algorithms for machine learning models, +e.g., layers for neural network models, optimizers/initializer/metric/loss for +general machine learning models.</p> +<img src="../_static/images/singav1-sw.png" align="center" width="500px"/> +<br/> +<span><strong>Figure 1 - SINGA V1 software stack.</strong></span><div class="section" id="core"> +<h2>Core<a class="headerlink" href="#core" title="Permalink to this headline">¶</a></h2> +<p><a class="reference external" href="tensor.html">Tensor</a> and <a class="reference external" href="device.html">Device</a> are two core abstractions in SINGA. Tensor class represents a +multi-dimensional array, which stores model variables and provides linear algebra +operations for machine learning +algorithms, including matrix multiplication and random functions. Each tensor +instance (i.e. a tensor) is allocated on a Device instance. +Each Device instance (i.e. a device) is created against one hardware device, +e.g. a GPU card or a CPU core. Devices manage the memory of tensors and execute +tensor operations on its execution units, e.g. CPU threads or CUDA streams.</p> +<p>Depending on the hardware and the programming language, SINGA have implemented +the following specific device classes:</p> +<ul class="simple"> +<li><strong>CudaGPU</strong> represents an Nvidia GPU card. The execution units are the CUDA streams.</li> +<li><strong>CppCPU</strong> represents a normal CPU. The execution units are the CPU threads.</li> +<li><strong>OpenclGPU</strong> represents normal GPU card from both Nvidia and AMD. +The execution units are the CommandQueues. Given that OpenCL is compatible with +many hardware devices, e.g. FPGA and ARM, the OpenclGPU has the potential to be +extended for other devices.</li> +</ul> +<p>Different types of devices use different programming languages to write the kernel +functions for tensor operations,</p> +<ul class="simple"> +<li>CppMath (tensor_math_cpp.h) implements the tensor operations using Cpp for CppCPU</li> +<li>CudaMath (tensor_math_cuda.h) implements the tensor operations using CUDA for CudaGPU</li> +<li>OpenclMath (tensor_math_opencl.h) implements the tensor operations using OpenCL for OpenclGPU</li> +</ul> +<p>In addition, different types of data, such as float32 and float16, could be supported by adding +the corresponding tensor functions.</p> +<p>Typically, users would create a device instance and pass it to create multiple +tensor instances. When users call the Tensor functions, these function would invoke +the corresponding implementation (CppMath/CudaMath/OpenclMath) automatically. In +other words, the implementation of Tensor operations is transparent to users.</p> +<p>Most machine learning algorithms could be expressed using (dense or sparse) tensors. +Therefore, with the Tensor abstraction, SINGA would be able to run a wide range of models, +including deep learning models and other traditional machine learning models.</p> +<p>The Tensor and Device abstractions are extensible to support a wide range of hardware device +using different programming languages. A new hardware device would be supported by +adding a new Device subclass and the corresponding implementation of the Tensor +operations (xxxMath).</p> +<p>Optimizations in terms of speed and memory could be implemented by Device, which +manages both operation execution and memory malloc/free. More optimization details +would be described in the <a class="reference external" href="device.html">Device page</a>.</p> +</div> +<div class="section" id="model"> +<h2>Model<a class="headerlink" href="#model" title="Permalink to this headline">¶</a></h2> +<p>On top of the Tensor and Device abstractions, SINGA provides some higher level +classes for machine learning modules.</p> +<ul class="simple"> +<li><a class="reference external" href="layer.html">Layer</a> and its subclasses are specific for neural networks. Every layer provides +functions for forward propagating features and backward propagating gradients w.r.t the training loss functions. +They wraps the complex layer operations so that users can easily create neural nets +by connecting a set of layers.</li> +<li><a class="reference external" href="initializer.html">Initializer</a> and its subclasses provide variant methods of initializing +model parameters (stored in Tensor instances), following Uniform, Gaussian, etc.</li> +<li><a class="reference external" href="loss.html">Loss</a> and its subclasses defines the training objective loss functions. +Both functions of computing the loss values and computing the gradient of the prediction w.r.t the +objective loss are implemented. Example loss functions include squared error and cross entropy.</li> +<li><a class="reference external" href="metric.html">Metric</a> and its subclasses provide the function to measure the +performance of the model, e.g., the accuracy.</li> +<li><a class="reference external" href="optimizer.html">Optimizer</a> and its subclasses implement the methods for updating +model parameter values using parameter gradients, including SGD, AdaGrad, RMSProp etc.</li> +</ul> +</div> +<div class="section" id="io"> +<h2>IO<a class="headerlink" href="#io" title="Permalink to this headline">¶</a></h2> +<p>The IO module consists of classes for data loading, data preprocessing and message passing.</p> +<ul class="simple"> +<li>Reader and its subclasses load string records from disk files</li> +<li>Writer and its subclasses write string records to disk files</li> +<li>Encoder and its subclasses encode Tensor instances into string records</li> +<li>Decoder and its subclasses decodes string records into Tensor instances</li> +<li>Endpoint represents a communication endpoint which provides functions for passing messages to each other.</li> +<li>Message represents communication messages between Endpoint instances. 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href="../index.html">incubator-singa</a> + + </nav> + + + <div class="wy-nav-content"> + + <div class="rst-content"> + + + + + + + + + + + + + + + + + +<div role="navigation" aria-label="breadcrumbs navigation"> + + <ul class="wy-breadcrumbs"> + + <li><a href="../index.html">Docs</a> »</li> + + <li><a href="index.html">Documentation</a> »</li> + + <li>Tensor</li> + + + <li class="wy-breadcrumbs-aside"> + + + + </li> + + </ul> + + + <hr/> +</div> + <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article";> + <div itemprop="articleBody"> + + <div class="section" id="tensor"> +<h1>Tensor<a class="headerlink" href="#tensor" title="Permalink to this headline">¶</a></h1> +<p>Each Tensor instance is a multi-dimensional array allocated on a specific +Device instance. Tensor instances store variables and provide +linear algebra operations over different types of hardware devices without user +awareness. Note that users need to make sure the tensor operands are +allocated on the same device except copy functions.</p> +<div class="section" id="tensor-implementation"> +<h2>Tensor implementation<a class="headerlink" href="#tensor-implementation" title="Permalink to this headline">¶</a></h2> +<p>SINGA has three different sets of implmentations of Tensor functions, one for each +type of Device.</p> +<ul class="simple"> +<li>âtensor_math_cpp.hâ implements operations using Cpp (with CBLAS) for CppGPU devices.</li> +<li>âtensor_math_cuda.hâ implements operations using Cuda (with cuBLAS) for CudaGPU devices.</li> +<li>âtensor_math_opencl.hâ implements operations using OpenCL for OpenclGPU devices.</li> +</ul> +</div> +<div class="section" id="python-api"> +<h2>Python API<a class="headerlink" href="#python-api" title="Permalink to this headline">¶</a></h2> +</div> +<div class="section" id="cpp-api"> +<h2>CPP API<a class="headerlink" href="#cpp-api" title="Permalink to this headline">¶</a></h2> +</div> +</div> + + + </div> + + </div> + <footer> + + <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation"> + + <a href="layer.html" class="btn btn-neutral float-right" title="Layer" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right"></span></a> + + + <a href="device.html" class="btn btn-neutral float-left" title="Device" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left"></span> Previous</a> + + </div> + + + <hr/> + + <div role="contentinfo"> + <p> + © Copyright 2019 The Apache Software Foundation. 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All other marks mentioned may be trademarks or registered trademarks of their respective owners. + + </p> + </div> + Built with <a href="http://sphinx-doc.org/";>Sphinx</a> using a <a href="https://github.com/rtfd/sphinx_rtd_theme";>theme</a> provided by <a href="https://readthedocs.org";>Read the Docs</a>. + +</footer> + + </div> + </div> + + </section> + + </div> + + + + <script type="text/javascript"> + jQuery(function () { + SphinxRtdTheme.Navigation.enable(true); + }); + </script> + + + + + + +<div class="rst-versions" data-toggle="rst-versions" role="note" aria-label="versions"> + <span class="rst-current-version" data-toggle="rst-current-version"> + <span class="fa fa-book"> incubator-singa </span> + v: latest + <span class="fa fa-caret-down"></span> + </span> + <div class="rst-other-versions"> + <dl> + <dt>Languages</dt> + <dd><a href=".././index.html">English</a></dd> + <dd><a href=".././zh/index.html">ä¸æ</a></dd> + </dl> + <dl> + <dt>Versions</dt> + <dd><a 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href="metric.html">Metric</a></li> +<li class="toctree-l2"><a class="reference internal" href="optimizer.html">Optimizer</a></li> +<li class="toctree-l2"><a class="reference internal" href="autograd.html">Autograd in Singa</a></li> +<li class="toctree-l2"><a class="reference internal" href="data.html">Data</a></li> +<li class="toctree-l2"><a class="reference internal" href="image_tool.html">Image Tool</a></li> +<li class="toctree-l2"><a class="reference internal" href="snapshot.html">Snapshot</a></li> +<li class="toctree-l2"><a class="reference internal" href="converter.html">Caffe Converter</a></li> +<li class="toctree-l2 current"><a class="current reference internal" href="#">Utils</a></li> +<li class="toctree-l2"><a class="reference internal" href="model_zoo/index.html">Model Zoo</a></li> +<li class="toctree-l2"><a class="reference internal" href="security.html">Security</a></li> +</ul> +</li> +<li class="toctree-l1"><a class="reference internal" href="../downloads.html">Download SINGA</a></li> +</ul> +<p class="caption"><span class="caption-text">Development</span></p> +<ul> +<li class="toctree-l1"><a class="reference internal" href="../develop/schedule.html">Development Schedule</a></li> +<li class="toctree-l1"><a class="reference internal" href="../develop/how-contribute.html">How to Contribute to SINGA</a></li> +<li class="toctree-l1"><a class="reference internal" href="../develop/how-contribute.html#how-to-become-a-singa-committer">How to become a SINGA committer</a></li> +<li class="toctree-l1"><a class="reference internal" href="../develop/contribute-code.html">How to Contribute Code</a></li> +<li class="toctree-l1"><a class="reference internal" href="../develop/contribute-docs.html">How to Contribute to Documentation</a></li> +<li class="toctree-l1"><a class="reference internal" href="../develop/how-to-release.html">How to prepare a release</a></li> +</ul> +<p class="caption"><span class="caption-text">Community</span></p> +<ul> +<li class="toctree-l1"><a class="reference internal" href="../community/source-repository.html">Source Repository</a></li> +<li class="toctree-l1"><a class="reference internal" href="../community/mail-lists.html">Project Mailing Lists</a></li> +<li class="toctree-l1"><a class="reference internal" href="../community/issue-tracking.html">Issue Tracking</a></li> +<li class="toctree-l1"><a class="reference internal" href="../community/team-list.html">The SINGA Team</a></li> +</ul> + + + + </div> + </div> + </nav> + + <section data-toggle="wy-nav-shift" class="wy-nav-content-wrap"> + + + <nav class="wy-nav-top" aria-label="top navigation"> + + <i data-toggle="wy-nav-top" class="fa fa-bars"></i> + <a href="../index.html">incubator-singa</a> + + </nav> + + + <div class="wy-nav-content"> + + <div class="rst-content"> + + + + + + + + + + + + + + + + + +<div role="navigation" aria-label="breadcrumbs navigation"> + + <ul class="wy-breadcrumbs"> + + <li><a href="../index.html">Docs</a> »</li> + + 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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. +--><div class="section" id="download-singa"> +<h1>Download SINGA<a class="headerlink" href="#download-singa" title="Permalink to this headline">¶</a></h1> +<ul> +<li><p class="first">To verify the downloaded tar.gz file, download the KEY and ASC files and then execute the following commands</p> +<div class="highlight-default notranslate"><div class="highlight"><pre><span></span> <span class="o">%</span> <span class="n">gpg</span> <span class="o">--</span><span class="kn">import</span> <span class="nn">KEYS</span> + <span class="o">%</span> <span class="n">gpg</span> <span class="o">--</span><span class="n">verify</span> <span class="n">downloaded_file</span><span class="o">.</span><span class="n">asc</span> <span class="n">downloaded_file</span> +</pre></div> +</div> +<p>You can also check the SHA512 or MD5 values to see if the download is completed.</p> +</li> +<li><p class="first">v2.0.0 (20 April 2019):</p> +<ul class="simple"> +<li><a class="reference external" href="http://www.apache.org/dyn/closer.cgi/incubator/singa/2.0.0/apache-singa-incubating-2.0.0.tar.gz";>Apache SINGA 2.0.0</a> +<a class="reference external" href="https://www.apache.org/dist/incubator/singa/2.0.0/apache-singa-incubating-2.0.0.tar.gz.sha512";>[SHA512]</a> +<a class="reference external" href="https://www.apache.org/dist/incubator/singa/2.0.0/KEYS";>[KEYS]</a> +<a class="reference external" href="https://www.apache.org/dist/incubator/singa/2.0.0/apache-singa-incubating-2.0.0.tar.gz.asc";>[ASC]</a></li> +<li><a class="reference external" href="releases/RELEASE_NOTES_2.0.0.html">Release Notes 2.0.0</a></li> +<li>New features and major updates,<ul> +<li>Enhance autograd (for Convolution networks and recurrent networks)</li> +<li>Support ONNX</li> +<li>Improve the CPP operations via Intel MKL DNN lib</li> +<li>Implement tensor broadcasting</li> +<li>Move Docker images under Apache user name</li> +<li>Update depdent lib versions in conda-build config</li> +</ul> +</li> +</ul> +</li> +<li><p class="first">v1.2.0 (6 June 2018):</p> +<ul class="simple"> +<li><a class="reference external" href="https://archive.apache.org/dist/incubator/singa/1.2.0/apache-singa-incubating-1.2.0.tar.gz";>Apache SINGA 1.2.0</a> +<a class="reference external" href="https://www.apache.org/dist/incubator/singa/1.2.0/apache-singa-incubating-1.2.0.tar.gz.sha512";>[SHA512]</a> +<a class="reference external" href="https://www.apache.org/dist/incubator/singa/1.2.0/KEYS";>[KEYS]</a> +<a class="reference external" href="https://www.apache.org/dist/incubator/singa/1.2.0/apache-singa-incubating-1.2.0.tar.gz.asc";>[ASC]</a></li> +<li><a class="reference external" href="releases/RELEASE_NOTES_1.2.0.html">Release Notes 1.2.0</a></li> +<li>New features and major updates,<ul> +<li>Implement autograd (currently support MLP model)</li> +<li>Upgrade PySinga to support Python 3</li> +<li>Improve the Tensor class with the stride field</li> +<li>Upgrade cuDNN from V5 to V7</li> +<li>Add VGG, Inception V4, ResNet, and DenseNet for ImageNet classification</li> +<li>Create alias for conda packages</li> +<li>Complete documentation in Chinese</li> +<li>Add instructions for running Singa on Windows</li> +<li>Update the compilation, CI</li> +<li>Fix some bugs</li> +</ul> +</li> +</ul> +</li> +<li><p class="first">v1.1.0 (12 February 2017):</p> +<ul class="simple"> +<li><a class="reference external" href="https://archive.apache.org/dist/incubator/singa/1.1.0/apache-singa-incubating-1.1.0.tar.gz";>Apache SINGA 1.1.0</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/1.1.0/apache-singa-incubating-1.1.0.tar.gz.md5";>[MD5]</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/1.1.0/KEYS";>[KEYS]</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/1.1.0/apache-singa-incubating-1.1.0.tar.gz.asc";>[ASC]</a></li> +<li><a class="reference external" href="releases/RELEASE_NOTES_1.1.0.html">Release Notes 1.1.0</a></li> +<li>New features and major updates,<ul> +<li>Create Docker images (CPU and GPU versions)</li> +<li>Create Amazon AMI for SINGA (CPU version)</li> +<li>Integrate with Jenkins for automatically generating Wheel and Debian packages (for installation), and updating the website.</li> +<li>Enhance the FeedFowardNet, e.g., multiple inputs and verbose mode for debugging</li> +<li>Add Concat and Slice layers</li> +<li>Extend CrossEntropyLoss to accept instance with multiple labels</li> +<li>Add image_tool.py with image augmentation methods</li> +<li>Support model loading and saving via the Snapshot API</li> +<li>Compile SINGA source on Windows</li> +<li>Compile mandatory dependent libraries together with SINGA code</li> +<li>Enable Java binding (basic) for SINGA</li> +<li>Add version ID in checkpointing files</li> +<li>Add Rafiki toolkit for providing RESTFul APIs</li> +<li>Add examples pretrained from Caffe, including GoogleNet</li> +</ul> +</li> +</ul> +</li> +<li><p class="first">v1.0.0 (8 September 2016):</p> +<ul class="simple"> +<li><a class="reference external" href="https://archive.apache.org/dist/incubator/singa/1.0.0/apache-singa-incubating-1.0.0.tar.gz";>Apache SINGA 1.0.0</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/1.0.0/apache-singa-incubating-1.0.0.tar.gz.md5";>[MD5]</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa//1.0.0/KEYS";>[KEYS]</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/1.0.0/apache-singa-incubating-1.0.0.tar.gz.asc";>[ASC]</a></li> +<li><a class="reference external" href="releases/RELEASE_NOTES_1.0.0.html">Release Notes 1.0.0</a></li> +<li>New features and major updates,<ul> +<li>Tensor abstraction for supporting more machine learning models.</li> +<li>Device abstraction for running on different hardware devices, including CPU, (Nvidia/AMD) GPU and FPGA (to be tested in later versions).</li> +<li>Replace GNU autotool with cmake for compilation.</li> +<li>Support Mac OS</li> +<li>Improve Python binding, including installation and programming</li> +<li>More deep learning models, including VGG and ResNet</li> +<li>More IO classes for reading/writing files and encoding/decoding data</li> +<li>New network communication components directly based on Socket.</li> +<li>Cudnn V5 with Dropout and RNN layers.</li> +<li>Replace website building tool from maven to Sphinx</li> +<li>Integrate Travis-CI</li> +</ul> +</li> +</ul> +</li> +<li><p class="first">v0.3.0 (20 April 2016):</p> +<ul class="simple"> +<li><a class="reference external" href="https://archive.apache.org/dist/incubator/singa/0.3.0/apache-singa-incubating-0.3.0.tar.gz";>Apache SINGA 0.3.0</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/0.3.0/apache-singa-incubating-0.3.0.tar.gz.md5";>[MD5]</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/0.3.0/KEYS";>[KEYS]</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/0.3.0/apache-singa-incubating-0.3.0.tar.gz.asc";>[ASC]</a></li> +<li><a class="reference external" href="releases/RELEASE_NOTES_0.3.0.html">Release Notes 0.3.0</a></li> +<li>New features and major updates,<ul> +<li><a class="reference external" href="v0.3.0/gpu.html">Training on GPU cluster</a> enables training of deep learning models over a GPU cluster.</li> +<li><a class="reference external" href="v0.3.0/python.html">Python wrapper improvement</a> makes it easy to configure the job, including neural net and SGD algorithm.</li> +<li><a class="reference external" href="v0.3.0/updater.html">New SGD updaters</a> are added, including Adam, AdaDelta and AdaMax.</li> +<li><a class="reference external" href="v0.3.0/installation.html">Installation</a> has fewer dependent libraries for single node training.</li> +<li>Heterogeneous training with CPU and GPU.</li> +<li>Support cuDNN V4.</li> +<li>Data prefetching.</li> +<li>Fix some bugs.</li> +</ul> +</li> +</ul> +</li> +<li><p class="first">v0.2.0 (14 January 2016):</p> +<ul class="simple"> +<li><a class="reference external" href="https://archive.apache.org/dist/incubator/singa/0.2.0/apache-singa-incubating-0.2.0.tar.gz";>Apache SINGA 0.2.0</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/0.2.0/apache-singa-incubating-0.2.0.tar.gz.md5";>[MD5]</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/0.2.0/KEYS";>[KEYS]</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/0.2.0/apache-singa-incubating-0.2.0.tar.gz.asc";>[ASC]</a></li> +<li><a class="reference external" href="releases/RELEASE_NOTES_0.2.0.html">Release Notes 0.2.0</a></li> +<li>New features and major updates,<ul> +<li><a class="reference external" href="v0.2.0/gpu.html">Training on GPU</a> enables training of complex models on a single node with multiple GPU cards.</li> +<li><a class="reference external" href="v0.2.0/hybrid.html">Hybrid neural net partitioning</a> supports data and model parallelism at the same time.</li> +<li><a class="reference external" href="v0.2.0/python.html">Python wrapper</a> makes it easy to configure the job, including neural net and SGD algorithm.</li> +<li><a class="reference external" href="v0.2.0/general-rnn.html">RNN model and BPTT algorithm</a> are implemented to support applications based on RNN models, e.g., GRU.</li> +<li><a class="reference external" href="v0.2.0/distributed-training.html">Cloud software integration</a> includes Mesos, Docker and HDFS.</li> +<li>Visualization of neural net structure and layer information, which is helpful for debugging.</li> +<li>Linear algebra functions and random functions against Blobs and raw data pointers.</li> +<li>New layers, including SoftmaxLayer, ArgSortLayer, DummyLayer, RNN layers and cuDNN layers.</li> +<li>Update Layer class to carry multiple data/grad Blobs.</li> +<li>Extract features and test performance for new data by loading previously trained model parameters.</li> +<li>Add Store class for IO operations.</li> +</ul> +</li> +</ul> +</li> +<li><p class="first">v0.1.0 (8 October 2015):</p> +<ul class="simple"> +<li><a class="reference external" href="https://archive.apache.org/dist/incubator/singa/apache-singa-incubating-0.1.0.tar.gz";>Apache SINGA 0.1.0</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/apache-singa-incubating-0.1.0.tar.gz.md5";>[MD5]</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/KEYS";>[KEYS]</a> +<a class="reference external" href="https://archive.apache.org/dist/incubator/singa/apache-singa-incubating-0.1.0.tar.gz.asc";>[ASC]</a></li> +<li><a class="reference external" href="https://console.aws.amazon.com/ec2/v2/home?region=ap-southeast-1#LaunchInstanceWizard:ami=ami-b41001e6";>Amazon EC2 image</a></li> +<li><a class="reference external" href="releases/RELEASE_NOTES_0.1.0.html">Release Notes 0.1.0</a></li> +<li>Major features include,<ul> +<li>Installation using GNU build utility</li> +<li>Scripts for job management with zookeeper</li> +<li>Programming model based on NeuralNet and Layer abstractions.</li> +<li>System architecture based on Worker, Server and Stub.</li> +<li>Training models from three different model categories, namely, feed-forward models, energy models and RNN models.</li> +<li>Synchronous and asynchronous distributed training frameworks using CPU</li> +<li>Checkpoint and restore</li> +<li>Unit test using gtest</li> +</ul> +</li> +</ul> +</li> +</ul> +<p><strong>Disclaimer</strong></p> +<p>Apache SINGA is an effort undergoing incubation at The Apache Software +Foundation (ASF), sponsored by the name of Apache Incubator PMC. Incubation is +required of all newly accepted projects until a further review indicates that +the infrastructure, communications, and decision making process have stabilized +in a manner consistent with other successful ASF projects. While incubation +status is not necessarily a reflection of the completeness or stability of the +code, it does indicate that the project has yet to be fully endorsed by the +ASF.</p> +</div> + + + </div> + + </div> + <footer> + + <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation"> + + <a href="develop/schedule.html" class="btn btn-neutral float-right" title="Development Schedule" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right"></span></a> + + + <a href="docs/security.html" class="btn btn-neutral float-left" title="Security" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left"></span> Previous</a> + + </div> + + + <hr/> + + <div role="contentinfo"> + <p> + © Copyright 2019 The Apache Software Foundation. All rights reserved. Apache SINGA, Apache, the Apache feather logo, and the Apache SINGA project logos are trademarks of The Apache Software Foundation. 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