multicoreware parallel path analyzer...

MulticoreWare

Parallel Path Analyzer (PPA)

Hui Huang, Chunpeng Zhang, Yao Wang, Lihua Zhang

6/13/11 Copyright (C) 2011 MulticoreWare Inc

• What is Parallel Path Analyzer?

• PPA overview

• Developer Library overview

• Story 1: Instrument codes with the developer library

• Story 2: Data collecting and viewing

• Story3: Data post-processing

• Performance optimization example with PPA

• Other outlined features & future enhancements

• Q&A

6/13/11 2 Copyright (C) 2011 MulticoreWare Inc

Agenda

• A platform-independent standalone tool for analyzing applications on a heterogeneous computing system

• Identify system-wide performance bottlenecks and find critical paths of the applications, whether it is in CPU, GPU, or I/O

• Target both traditional discrete CPU/GPU based and APU-accelerated OpenCL & Non-OpenCL applications

• Visualize profiling data in intuitive graphs and generates meaningful numerical results

• Seamlessly integrate with other MulticareWare tools to provide comprehensive toolset to ease complex heterogeneous computing development


What is Parallel Path Analyzer?


• PPA overview


• Story 1: Add user-level library

• Story 2: Events captured and viewed

• Story3: Data processing



• Q&A


Agenda

• Provide a user-level library for developer to instrument CPU code by manual and automatic ways

• Automatic capture of full trace of OpenCL API and commands – Common trace format with AMD tools

• A virtual global system clock mechanism is used to create time synchronized performance view across CPUs/GPUs

• Support debugging & statistic events

• User friendly GUI and comprehensive data views to help developer understand the behavior of the applications


PPA Overview – Key Features

• Simultaneous multiple applications profiling support – Complicated app which includes independent but dependent modules

that could be even developed by different developers, or even different vendors

– DirectShow filters based app is such an example

• Exclusive AMD OpenCL sub-kernel profiling & debugging capability (to be avail soon) – Identify load balancing issues between workgroup/wavefront

– Identify critical path within a kernel (which segments of code is bottleneck)

– Debug events allowed to help run-time debug

• Fusion Supports – power & bandwidth measurement (will be avail soon)


PPA Overview – Key Features

• Developer / User Level Library – PPA initialization APIs & profiling APIs

– Runtime DLL

• GUI – Provide user friendly interface for all major operations

– Provide comprehensive & intuitive graph view to visualize profiling data


PPA Overview – Main Components


PPA Overview – Main GUI

• Event – i.e. profiling event in PPA is a data structure, which has

• A unique event name / ID to identify itself

• An event type to identify its meaning, e.g. start, stop of a CPU event, debug event

• A globalized timestamp to record its occurrence time

• Other info depending on its type, e.g., – CPU event: Start time, stop time, core ID, thread ID & priority

– GPU event: device ID, queued time, submit time, start time, stop time of CL command

– Essential element to measure which has performance meaning, like start and stop of an subroutine in CPU code user is interested in

– Essential element to draw in PPA viewer


Some PPA Terms

• Frame – In default all events are drawn in single view window

– For Bullet type of apps which is timestep based and same pipeline repeats every timestep.

– Performance is varying between frames and target is const perf over frames

• Session – A session records results from a single data collection operation

• including the raw profiling data dumped from app runtime as well post processing results

– PPA will automatically generate a new session for each data collection operation, and user can quickly guide between sessions to check / process historical data


Some PPA Terms

• Bullet – An open source project for game physics simulation

– Its core feature is rigid body dynamics, but also support effect physics like particles & softbody

– We’ll use AMD Opencl version of Bullet particle demo to introduce PPA & demonstrate how PPA can be used to optimize a heterogeneous app, because,

• It uses both CPU & GPU, and there is dependency in between

• GPU is used for both simulation & rendering

• It is a natural frame based application


Bullet as Sample


• PPA overview







• Q&A


Agenda

Library files

• ppa.dll – PPA developer library (user-level runtime)

• ppa.h – Declarations of PPA_INIT and PPA_END,

– Other user level profiling APIs, like PPAStopCpuEventFunc(e)

• ppa.cpp – Implementation of PPA initialization

• ppaEventDefs.h – User-defined events

Copyright (C) 2011 MulticoreWare Inc

Developer Library Overview

• Define the events

PPA_DEFINE_EVENT(your-event-name)

• Declare & initialize the lib

PPA_DECLARE_EVENT;

PPA_INIT();

• Instrument the application codes by using paired routines

//beginning of the code block

ppaStartCpuEventFuc(your-event-name)

…

ppaStopCpuEventFunc(your-event-name)

//end of the code bock

• Release the lib

PPA_END();

6/13/11

Developer Library Overview


• PPA overview







• Q&A


Agenda

#include "ppa.h"

PPA_DECLARE_EVENT;

int main(int argc,char** argv)

{

// Call PPA_INIT() to initialize ppaUtil

PPA_INIT();

ParticlesDemo pDemo(argc, argv);

pDemo.initPhysics();

pDemo.getDynamicsWorld()->setDebugDrawer(&gDebugDrawer);

glutmain(argc, argv,640,480,"Bullet Physics Demo. http://bulletphysics.com", &pDemo);

// Call PPA_END() to terminate ppaUtil

PPA_END();

return 0;

}

6/13/11

Developer Library Use in Bullet

Event declaration in ppaEventDefs.h

PPA_DEFINE_EVENT(btDemo_renderme)

:

PPA_DEFINE_EVENT(btPart_runIntegrateMotionKernel)

PPA_DEFINE_EVENT(btPart_runCollideParticlesKernel)

:

Profiling code in CPU code: void ParticlesDemo::renderme()

{

PPAStartCpuEventFunc(btDemo_renderme);

glColor3f(1.0, 1.0, 1.0);

:

PPAStopCpuEventFunc(btDemo_renderme);

}

6/13/11

Developer Library Use in Bullet


• PPA overview


• Story 1: Instrument codes with developer library


• Story 3: Data post processing



• Q&A

6/13/11

Agenda


PPA Data Collection


PPA Data Viewer


• PPA overview




• Story 3: Data post-processing



• Q&A


Agenda


Data Post-processing – Framing


Data Post-processing – Extractor


• PPA overview







• Q&A


Agenda

• 5 stages of particle pipeline for each timestep (i.e. frame)

• Each stage has single or multiple kernel launches as well as data copy


Bullet capture before opt

• All clFinish calls except for runCollideParticlesKernel stage are removed

• Host is still blocked by last clFinish() and clEnqReadBuffer for CLInterop


Bullet capture after initial try

• In fact No ClFinish is needed since no data read is required till ClInterop

• Host is not blocked except for ClInterop; Main gaps are remove!


Bullet capture after opt


Bullet perf before & after opt


• PPA overview







• Q&A


Agenda

Special CL API calls removal for profiling perf concerns


Other outlined features – duplicated events removal

• Pause & resume profiling to profile interesting spots only – Reduce captured data size as well


Other outstanding features–

pause & resume profiling

• Allow profiling complicated applications consisting of independent modules



multiple app profiling capability



System Monitor

• Interoperability with TM and GMAC

– Visualizing task scheduling, load balancing/ migration, data transfer in TM and GMAC in an intuitive way

• Automatic CPU profiling events insertion

• Automatic critical path analysis

• GPU rendering profiling capability

6/13/11 Copyright (C) 2011, MulticoreWare Inc

Future enhancements


• Visit http://www.multicorewareinc.com to request closed beta application

• Contact email: [email protected]

http://www.multicorewareinc.com/

mailto:[email protected]

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