Gpu Recipe

7/30/2019 Gpu Recipe

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Recipe for running simpleCUDA code on a GPU based

Rocks cluster

GPU workshop

UR June 20,2008

Alice Quillen

Head node:sneth.pas.rochester.edu

http://astro.pas.rochester.edu/~aquillen/gpuworkshop.html


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Outline

The Kernel .cu CUDA files

Calling __global__ functions

Setting grids and threads

Allocating memory on device Compiling in emulate mode

Submitting a job to the queue using SGE Timing your job for benchmarks


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CUDA C, CU files

Routines that call the device must be in

plain C -- with extension .cu

Often 2 files1) The kernel -- .cu file containing routines that are

running on the device.

2) A .cu file that calls the routines from kernel.#includes the kernel

Optional additional .cpp or .c files withother routines can be linked


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Kernel, Threads + BlocksKernel has two different types of functions

__global__ called from host, executed on device__device__ called from device, run on device

__global__ void addone(float* d_array) // kernel is addone

{ int index = blockIdx.x * blockDim.x + threadIdx.x;d_array[index] += 1.0;

}

d_array must be allocated on devicethe above code loops over all threads and blocks

automaticallyon a CPU this would be inside a loop


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Calling a __global__ routinethreads and blocks

Calling the routine from the host to run on deviceint p = 256; // power of 2

dim3 threads = (p,1,1); // number of threads per block is pdim3 grid = (arraylength/p,1,1); // number of blocks is arraylength divided by the

// number of threads// arraylength is assumed a multiple of p

int sharedMemsize = 0;addone > (d_array); // call the kernel

Inside the routine blockDim.x is p (number of threads),threadIdx.x ranges from 0 to p-1, (covers all threads)blockIdx.x ranges from 0 to arraylength/p-1 (covers all blocks)

__global__ void addone(float * d_array)

{int index = blockIdx.x * blockDim.x + threadIdx.x;d_array[index] += 1.0;

}


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Memory allocation on deviceint lengthvector = 10240; // note multiple of 256, pad with zeros if your vector

// isnt a multipleunsigned int memSize = lengtharray*sizeof(float);

// allocate array on hostfloat* h_array = (float*) malloc(memSize);// array on host

float* d_array; // array on device// allocate array on device

CUDA_SAFE_CALL(cudaMalloc((void**)&d_array, memSize ));// CUDA_SAFE_CALL utility Tool. If an error is found, it prints out and error// message, file name, and line number in file where the error can be found

// Copy array from host to device

CUDA_SAFE_CALL(cudaMemcpy(d_array, h_array, memSize,cudaMemcpyHostToDevice));

// Copy array from device to hostCUDA_SAFE_CALL(cudaMemcpy(h_array, d_array, memSize,

cudaMemcpyDeviceToHost));


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Global Device Memory Keep track of what data is on device and

on host

If you address host memory from device

then the code doesnt work


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A code that adds 1 to every element of alarge array on the GPU

#include // CUDA defined stuff#include// usual io

#include// contains kernelint main(int argc, char ** argv){

CUT_DEVICE_INIT();// device init, also will tell you if multiple devices// present

Allocate host array, fill it with somethingAllocate device arrayCopy array from host to deviceLaunch kernelCopy array back from device to host

Print out some of it out so you can see that the device didsomethingCUDA_SAFE_CALL(cudaFree(d_vector));// free memoryCUT_EXIT(argc, argv);// Use CUDA Utility Tool to exit cleanly

}


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CompilingSample head of Makefile

# name of executableEXECUTABLE := addone# Cuda source files (compiled with cudacc) don't put kernel

in as is included in other file

CUFILES := addone.cuCU_DEPS := addone_kernel.cu# C/C++ source files (compiled with gcc / c++)CCFILES :=

C_DEPS :=ROOTDIR = /usr/local/NVIDIA_CUDA_SDK/common/include $(ROOTDIR)/common.mk # SDK make


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Emulator[aquillen@sneth ~]$ make emu=1Makes executable code that runs on the CPU not on device

executable can be run on head node (which lacks GPUs)not necessary to send a job to queuein addone_kernel.cu:__global__ void addone(float* d_array)

{ int index = blockIdx.x * blockDim.x + threadIdx.x;d_array[index] += 1.0;printf(%.2e\n,d_array[index]);// emulator only!

}

Will not run or compile for device. Will run and compile in emulator.Prints for every block and thread.If (threadIdx.x == 0) printf(%.2e\n,d_array[index]); // much more manageable!


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Debugging Code that works in emulator mode may

not work on device (particularly memoryaccess, synch problems)

However debugging in emulator mode is apretty good way to get closer to workingcode

Profiler recently available, but we have notyet had a chance to play with it.


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Queue system SGE = Sun Grid Engine is an open source

batch-queuing system supported by SUN and itcomes as a roll with ROCKS

Rocks is an open-source Linux cluster

distribution that enables end users to easily buildcomputational clusters. CUDA comes as a roll.

To submit a job

[aquillen@sneth ~]$ qsub sge.bash

where sge.bash is a text file that looks like


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Example sge.bash file#!/bin/bash remind me that this uses bash shell##$ -cwd use current directory

#$ -o std.out stdout goes into this file#$ -e std.err stderr goes into this file#$ -S /bin/bash specify bash shell#$ -m be email at begin and end of job#$ -M [email protected] where to send email

#$ -N gal10 name of job#$ -l h_rt=24:00:00 let it run no more than 24 hours#$ -V something about exporting env variables

date +%s time in seconds for simple bench mark

# execute some code comment/home/aquillen/galint/exe/release/mkgal.out executables/home/aquillen/galint/exe/release/galintdate print datedate +%s

echo complete


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queue commands qstat look at what jobs are running

qdel 701 kill that job

qhost check all the nodes qstat j 703 explain to me what is going on

with that job


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Workshophttp://astro.pas.rochester.edu/~aquillen/gpuworkshop/assigna.html

Assignment #1 Submitting a job to the queue using SGE qsub Here is a sample sge (Grid Engine) file that is written in bash shell. sge.bash Transfer this file to your home directory on our rocks cluster sneth.pas.rochester.edu. Modify the file sge.bash so that it will print "hello, World" into a file called std.out and will sleep for 60 seconds or

so.

Submit it as a job to the queue (qsub sge.bash). Check the queue status to make sure your job is run (qstat).Assignment #2 Compiling and running the routine addone that adds 1 to every element in a large array Here is a sample kernel addone_kernel.cu

Here is a routine that calls this kernel addone.cuA Makefile to compile it MakefileA sge bash file to send it to the queue cudasge.bash

Transfer the above 4 files to your home directory on sneth. They can also be copied directly from the directory

~aquillen/addone/ on sneth. Edit the cudasge.bash file so it is appropriate for you. Compile the code with make. The executable will be in a subdirectory called release. Run it by submitting the

cudasge.bash file to the queue. Compile the code in emulate model (make emu=1). The executable will be in a subdirectory called emurelease.

Run this code. It will run on the head node so you don't need to submit it to the queue.Assignment #3 Write your own routine by modifying the above addone routines. Modify the kernel so that it computes the derivative of the array using a finite difference (f[i+1]-f[i]).

You will need an input and output arrays as arguments to your __global__ routine in the kernel as the order thatthreads and blocks executed is not specified.

You do not want to address memory outside the array as this will crash the code. If you check the addressing withan ifstatement your routine will take twice as long to run. Try to write the routine without an if statement. Hint: youcan trade an irrelevant amount of device global memory for the if statement.

Assignment #4 Discuss how you could implement a box smooth or 1d convolution routine


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BenchmarkingThere are many ways to time routines. Here is the one usedin the SDK. I think it uses sys/math.h gettimeofday() in linux

// initialize a timerunsigned int timer = 0;CUT_SAFE_CALL(cutCreateTimer(&timer));// start itCUT_SAFE_CALL(cutStartTimer(timer));

//// run your code here

//// Stop the timerCUT_SAFE_CALL(cutStopTimer(timer));printf( "Processing time: %f (ms)\n", cutGetTimerValue(timer));// time in milliseconds, returned as a float// Delete the timerCUT_SAFE_CALL(cutDeleteTimer(timer));


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Links

http://astro.pas.rochester.edu/~aquillen/gpuworkshop.htmlIncludes links to the CUDA manual, the SDK (software devel kit, lots ofgood programming examples) and other on line tutorials

Documents

Gpu Recipe