Hi guys, I should have done this before...
I checked out the latest snapshot from trunk and my test works fine now. Cheers :) Richard Gomes M: +44(77)9955-6813 http://tinyurl.com/frgomes twitter: frgomes JQuantLib is a library for Quantitative Finance written in Java. http://www.jquantlib.org/ twitter: jquantlib On 08/12/10 21:57, Richard Gomes wrote: > Hi guys, > > I have several tests which have copied/pasted code like this: > > static def calc( > p : Place, n : Int, > params : RemoteArray[Float]{home==p,rank==1}, > result : RemoteArray[Float]{home==p,rank==1}) { > val blocks = p.isCUDA() ? 480 : 1; > val threads = 512; > finish async at (p) @CUDA @CUDADirectParams { > finish > for ([block] in 0..blocks-1) async { > clocked finish > for ([thread] in 0..threads-1) clocked async { > val tid = block * threads + thread; > val tids = blocks * threads; > for (var i:int = tid; i< n; i += tids) { > val d = params(i); > result(i) = d * d;; > } > } > } > } > } > > ... which works fine. > > > One of the tests call the "calc" function above more or less like this: > > > finish { > for (gpu in gpus.values()) async at (cpu) { > ... > //--- First step : allocate device arrays > val gpuDatum = CUDAUtilities.makeRemoteArray[Float] > (gpu, len, (j:int) => cpuDatum(size/n * i + j)); > val gpuResult = CUDAUtilities.makeRemoteArray[Float] > (gpu, len, (j:int) => 0.0 as Float); > > //--- Second step : call kernel function > calc(gpu, len, gpuDatum, gpuResult); > > ... > } > > > > This example "works" but does not offer any coordination between gpus > connected to "cpu" (=here). > > Once I still have only one gpu at the moment, I defined > > export X10RT_ACCELS=CUDA0,CUDA0,CUDA0,CUDA0 > > When I tried to create another example employing teams like KMeansCUDA > does, it got stuck because all gpus share the same parent (=here). > > So, looks like (I guess) that Team is good for coordination between > different cpus, once the code is typically host code and not kernel code. > > OK. Then I tried coordination using clocks in different ways. > In the example below I explicitly declare and employ a certain clock for > coordinating tasks. > > > finish async { > val c = Clock.make(); > for (gpu in gpus.values()) async clocked (c) { > > val i = (gpu==cpu) ? cpu.id : gpu.id - Place.MAX_PLACES; > val len = size/n + ( i+1==n ? size%n : 0 ); > > //--- First step : allocate device arrays > > c.next(); > val gpuDatum = ... > val gpuResult = ... > > //--- Second step : call kernel function > > c.next(); > calc(gpu, len, gpuDatum, gpuResult); > > ... > } > } > > > Executing this example I've got the following message > > X10RT: async 37 is not a CUDA kernel. > > If I'm not wrong, this message comes from the kernel function, once this > message dissapears when I comment out the call to the kernel function. > > So, looks like there's a certain relationship between the "finish" in > the host code and the "finish" in the kernel code. > > In the documentation on Finish (pg 160) it says that a "finish" waits > for termination of all activities spawned by "S". I'm certainly confused > by the implications of this statement, so I tried to simplify the code > above, like this: > > > clocked finish { > for (gpu in gpus.values()) async { > > val i = (gpu==cpu) ? cpu.id : gpu.id - Place.MAX_PLACES; > val len = size/n + ( i+1==n ? size%n : 0 ); > > //--- First step : allocate device arrays > > next; > val gpuDatum = ... > val gpuResult = ... > > //--- Second step : call kernel function > > next; > calc(gpu, len, gpuDatum, gpuResult); > > ... > } > } > > > When I execute it, the result is absolutely the same: > > X10RT: async 37 is not a CUDA kernel. > > > > So, could you guys guide me about this? > > 1. Am I correct to think that I cannot employ Team when 2 or more GPUs > belong to the same place? > > 2. What is the relationship between a finish in the host code and a > finish in the kernel code? Or maybe this question should be on "clock"s > instead on "finish"es ? > > 2. Would you recommend a explicit clock in order to avoid conflict with > the clock in the kernel function? > > Thanks a lot :) > ------------------------------------------------------------------------------ This SF Dev2Dev email is sponsored by: WikiLeaks The End of the Free Internet http://p.sf.net/sfu/therealnews-com _______________________________________________ X10-users mailing list X10-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/x10-users
