indicthreads-pune12-accelerating computation in html 5

7/30/2019 IndicThreads-Pune12-Accelerating Computation in HTML 5

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Accelerating computation in html 5

Ashish ShahSAS R&D INDIA


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Outline

Multicore Computing

Problem statement

Demo

Introduction to OpenCL and WebCL

Conclusion

References


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Multicore Computing


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Problem statement

Layout algorithm for node-linked graphs

AlgorithmLayout


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DEMO

Demo 1 Serial versionDemo 2 - Parallel version with multi-core CPU

Demo 3 - Parallel version with many-core GPU


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Performance analysis

Tim

ein

ms

Number of particles


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Introduction to OpenCL

OpenCompute Language, C- like language.

Framework for writing parallel algorithms

Heterogeneous platforms

Developed by Apple

Is an open standard and controlled by Khronosgroup


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Example of adding two vectors

_kernel add(a,b,c)

{

int i =get_global_id(); //get thread id

c[i]=a[i]+b[i];

}

For(i=1 to n)

c[i]= a[i]+b[i];

Serial version

Using OpenCL


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OpenCL -Platform

Device

Host

Host

Intel CPUGPU 2

ComputeDevice 1 (GPU1)

Compute unite (Cores)


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OpenCL-Execution Model

1. Kernel2. Work-items

3. Work group

4. ND-range

5. Program

6. Memoryobjects

7. Commandqueues

_kernel add(a,b,c)

{int i =get_global_id();//get thread/workitem id

c[i]=a[i]+b[i];

}


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Memory Model in OpenCL

Compute Device

Compute unit 0 Compute unit 1 Compute unit 2

Global Memory -DRAM

Global constant memory-DRAM

Local memory/cache Local memory/cache Local memory/cache

Private register Private register Private register

P i d l


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Programming model

1. Data parallel-single function on multiple data

2. Task parallel-Multiple functions on single data

O CL S k


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OpenCL Runtime

OpenCL Framework

OpenCL Stack

OpenCL Device (GPU/CPUhardware)

Devicedriver

Compiler

Applications

kernals

OpenCL-Api

HTML,.java,.NET,c,c++

String data

Java,c,.net,WebCL

contextMemoryApis

Commandqueues, bufferobjects, kernelexecution

E ti l D l t T k


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Essential Development Tasks

Parallelize Code KernelInitializeOpenCL

environment

Initiatekernels and

data

Executekernel

Read backdata to host

C-code with restrictions

E ti l D l t T k


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environment

Initiatekernels and

data

Executekernel


Query compute device Create context Compile kernels

E ti l D l t T k


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environment

Initiatekernels and

data

Executekernel


Create memory objects Map data structures to OpenCL

supported data structures. Initialize kernel parameters

E nti l D l nt T k


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environment

Initiatekernels and

data

Executekernel


Specify number of threads toexecute task

Trigger the execution of kernel-sync or async



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environment

Initiatekernels and

data

Executekernel


Map to application datastructure

Introduction to WebCL


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Introduction to WebCL

Java Script bindings for OpenCL

First announced in March 2011 by Khronos

API definition underway

Prototype plugin is available only for Firefox

browser

Binding OpenCL to WebCL


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Binding OpenCL to WebCL

CPU

Host application JavaScript

OpenCL Framework

WebCL

OpenCL

compliant

device

Coding with WebCL


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Coding with WebCLplatforms = WebCL.getPlatformIDs();

context = WebCL.createContextFromType([WebCL.CL_CONTEXT_PLATFORM,

platforms[0]], WebCL.CL_DEVICE_TYPE_CPU);devices = context .getContextInfo(WebCL.CL_CONTEXT_DEVICES);

program = context .createProgramWithSource(kernelSrc);

kernelfunction1 = program.createKernel(function1");

buffparam = context.createBuffer(WebCL.CL_MEM_READ_WRITE, bufSize);

cmdQueue = context.createCommandQueue(devices[0], 0);

cmdQueue.enqueueWriteBuffer(buffparam , true, 0, bufSize, parameter, []);

kernelfunction1.setKernelArg(0, buffparam , WebCL.types.float2);

cmdQueue.enqueueNDRangeKernel(kernelfunction1 , 1, [], totalWorkitems,

totalWorkgroups, []);cmdQueue.finish ();

cmdQueue.enqueueReadBuffer(xyz, true, 0, bufSize, xyzParam, []);

A li ti f O CL


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Applications of OpenCL

Database mining

Neural networks Physics based simulation,mechanics

Image processing

Speech processing Weather forecasting and climate research

Bioinformatics

Conclusion


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Conclusion

Significant performance gains in using OpenCLfor computations in client-side environmentslike HTML5

Algorithms need to be parallelizable

Further optimizations can be achieved by

exploiting memory model

Software/Hardware used in demo application


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Software/Hardware used in demo application

Hardware

Intel(R) Core(TM)2 Quad core CPU Q8400 @ 2.66GHzNvidia 160m Quadro 8 cores @ 580 MHz

Software

OpenCL runtime for CPU

http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/

OpenCL runtime for GPU

http://www.nvidia.com/object/quadro_nvs_notebook.html

WebCL plugin for Firefox

http://webcl.nokiaresearch.com/

References
http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/http://www.nvidia.com/object/quadro_nvs_notebook.htmlhttp://www.nvidia.com/object/quadro_nvs_notebook.htmlhttp://webcl.nokiaresearch.com/http://webcl.nokiaresearch.com/http://www.nvidia.com/object/quadro_nvs_notebook.htmlhttp://www.nvidia.com/object/quadro_nvs_notebook.htmlhttp://www.nvidia.com/object/quadro_nvs_notebook.htmlhttp://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/http://software.intel.com/en-us/articles/vcsource-tools-opencl-sdk/


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References

http://www.macresearch.org/opencl

http://en.wikipedia.org/wiki/GPGPU

http://www.khronos.org/webcl/
http://www.macresearch.org/openclhttp://en.wikipedia.org/wiki/GPGPUhttp://www.khronos.org/webcl/http://www.khronos.org/webcl/http://en.wikipedia.org/wiki/GPGPUhttp://www.macresearch.org/opencl

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