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GPU Ecosystem
Introduction & Case Study
Ofer Rosenberg
October 2013

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Content
 GPU Ecosystem
 Ecosystem on Mobile/Embedded Platforms
 NSIGHT - Tools case study
 Libraries

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Product
GPU Ecosystem
Software Product Development cycle:
The GPU Ecosystem role is to support, speedup, and
improve this cycle for GPU Compute
Design
Write
Code
Debug
Profile

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GPU Ecosystem
 Support writing code by:
 IDE integration – Compiler, Parser, Wizards
 Libraries: Math (BLAS, IPP-like, Matrix, etc.),
STL-like (Thrust, BOLT)
 Support Debugging by:
 IDE integration of the debugger (preferred)
 Provide usable execution control (breakpoints, pause/resume, etc.)
 Providing reliable memory view of various address spaces
 Support Profiling by:
 Provide two levels of profiling: System Tracing and Kernel Profiling
 System Tracing - quick highlighting of hotspots and device optimal access
 Statistical and TimeLine-based Kernel Profiling (using perf. counters)
Design
Write
Code
Debug
Profile

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Ecosystem on
Mobile/Embedded Platforms

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ARM MALI
 Part of ARM SoC
 OpenCL 1.1Full Profile (Linux, Android)
 Renderscript (Android only)
 OpenCL SDK – Samples, Tutorials, etc.
 No GPU debugging capability
 ARM DS-5 (Developer Suite 5)
 Eclipse IDE integration
 Compiler, Debugger (CPU only)
 System Trace – CPU & GPU
 Deep Profiling - CPU & GPU

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Intel Haswell GPU
 Part of Haswell (CPU & GPU)
 OpenCL 1.2 Full Profile
 Windows only for now (Linux @ alpha stage)
 OpenCL SDK
 Samples
 Tools: Kernel Builder, VS/Eclipse Integration, Offline Compiler, GDB support (CPU Only)
 No GPU debugging capability
 VTune Amplifier XE supports OpenCL (CPU & GPU)
 System level tracing (Application, Memory, Kernel launch)
 Kernel Profiling

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Intel BayTrail platform (Atom)
 BayTrail < 13W, BayTrail-M < 6.5W
 Vallyview SoC (Z37xx)
 GPU is based on Gen7 (same arch as IvyBridge)
 Same as previous slide:
 OpenCL 1.2 (windows only for now)
 OpenCL SDK
 VTune support
 System level tracing
 Kernel Profiling

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NVIDIA Tegra 5 ? (Codename: Logan)
 Disclaimer: Logan is due early 2014. Part of the information is speculations
 Development Boards and Samples available to selected customers
 Logan SoC – 2W
 ARM CPU A15 4+1 :speculated
 Kepler based GPU : verified
 CUDA Support : verified
 CUDA SDK – Dozens of samples
 CUDA Libraries: Thrust, cuBLAS, cuNVPP, etc.
 NSIGHT : speculated
 System Trace
 Profiling, Debugging

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NSIGHT
TOOLS CASE STUDY
Design
Write
Code
Debug
Profile

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Nsight Highlights
 “NVIDIA® Nsight™ is the ultimate development platform for heterogeneous
computing”
( Taken from Nsight page )
 IDE integration
 Windows – integration with Visual Studio
 Linux – specialized Eclipse version
 Debugging , System Trace , Profiling
 Graphics (DX, OpenGL)
 Computing (OpenCL, CUDA, C++ AMP)
 Profiling only on CUDA kernels
 Debug/Trace/Profile Information is highly shaped
 Highly efficient information fields, windows, diagrams
 Feedback from professional users is noticed

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Debugging
 Much more than “just integrated” with the IDE
 Shaped windows showing valuable info
Assembly (GPU!)
Variables across
all warpsVisible layout of the stopped thread

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Debugging – Eclipse edition
 Seems that Eclipse integration is deeper than Visual Studio
 Unified CPU / GPU Debugging
 Simultaneous visibility into both CPU and GPU state
 Multi-GPU support
Slides from: “CUDA Development Using NVIDIA Nsight,
Eclipse Edition” by David Goodwin, SC12
 Full GPU debugging
 Set kernel breakpoints
 Single-step, run until, etc.
 View values across multiple GPU
threads at the same time
 Examine thread, warp, block state
 Source and assembly level debugging

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System Trace

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Kernel Profiling
 Choose a kernel to profile
 Skip N kernels, Profile M kernels
 Choose “experiments”
 Experiment - Types of profiling/analysis
 NVIDIA runs each kernel launch dozens of times with the same data

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Profiling Results
 Experiment list
 Each experiment is a tabbed window
 Profiling information is shaped in graphs,
pie charts, diagrams, etc.
 Taking HW counters and shaping them to easy-
to-understand graphics
 Information targets known HW bottlenecks, Code
inefficiencies, etc.
 Amazingly shaped…

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Profiling Results
 The information provides a quick & easy methodic way to identify the performance
bottlenecks
1 2
3 4

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Eclipse Edition - Source Code Editor
 Project Templates
 CUDA code highlighting
 CUDA aware refactoring
 CUDA aware code completion and inline help

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LIBRARIES EXAMPLES

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CUDA Libraries – Part of the SDK
 cuFFT
 cuBLAS
 cuRAND
 cuSPARSE
 NPP (like IPP)
 Math Library
 Thrust (next slide)

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Thrust Library
 https://developer.nvidia.com/thrust
 Works on top of CUDA
 Open-source version is available at github
 http://thrust.github.io/
 Presentations:
 http://on-demand.gputechconf.com/gtc-
express/2011/presentations/introductiontothrust.pdf

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OPENCL LIBRARIES

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CLPP
 OpenCL Data Parallel Primitives Library (similar to thrust)
 Source : https://code.google.com/p/clpp/
 7 committers, last commit 1.5Y ago

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OpenCL BLAS
 OpenCL BLAS
 http://openclblas.sourceforge.net/
 Code is available here (GPLv2):
 http://sourceforge.net/projects/openclblas/

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ViennaCL
 BLAS implementation
 http://viennacl.sourceforge.net/
 Looks very promising

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REFERENCES

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Platform links:
 ARM
 Developer site : http://malideveloper.arm.com
 OpenCL tracing : http://malideveloper.arm.com/develop-for-mali/tools/mali-graphics-debugger/
 DS-5 suite : http://www.arm.com/products/tools/software-tools/ds-5/index.php
 OpenCL SDK : http://malideveloper.arm.com/develop-for-mali/sdks/mali-opencl-sdk/
 OpenCL developer guide:
 Online: http://infocenter.arm.com/help/index.jsp?topic=/com.arm.doc.dui0538e/index.html
 PDF: http://infocenter.arm.com/help/topic/com.arm.doc.dui0538e/DUI0538E_mali_t600_opencl_dg.pdf
 NVIDIA
 http://www.anandtech.com/show/7169/nvidia-demonstrates-logan-soc-mobile-kepler
 http://www.slashgear.com/nvidia-tegra-logan-detailed-with-game-changing-cuda-integration-19274630/
 http://www.ubergizmo.com/2013/07/nvidia-tegra-5-release-date-specs-news/

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Links:
 Intel
 OpenCL sdk http://software.intel.com/en-us/vcsource/tools/opencl-sdk
 GPA http://software.intel.com/en-us/vcsource/tools/intel-gpa
 vTune support in OpenCL http://software.intel.com/en-us/articles/intel-vtune-amplifier-xe-getting-started-with-opencl-
performance-analysis-on-intel-hd-graphics
 http://www.theinquirer.net/inquirer/news/2266966/intel-releases-opencl-sdk-for-windows-and-linux
 Haswell Linux support: http://www.phoronix.com/scan.php?page=news_item&px=MTA3NDc
 OpenCL “Beignet” – open source linux compiler :
 http://software.intel.com/en-us/forums/topic/402118
 http://linux.slashdot.org/story/13/04/16/014233/intel-releases-new-opencl-implementation-for-gnulinux
 ATOM BayTrail:
 http://arstechnica.com/gadgets/2013/02/intel-gets-aggressive-with-new-smartphone-and-tablet-chips/
 http://www.anandtech.com/show/7314/intel-baytrail-preview-intel-atom-z3770-tested
 http://www.tomshardware.com/reviews/bay-trail-celeron-j1750-performance,3614-6.html
 http://software.intel.com/en-us/forums/topic/476221
 http://en.wikipedia.org/wiki/List_of_Intel_Atom_microprocessors#.22Bay_Trail.22_.2822_nm.29

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NSIGHT Links
 http://www.nvidia.com/object/nsight.html
 https://developer.nvidia.com/nsight-visual-studio-edition-videos
 https://developer.nvidia.com/developer-webinars
 http://on-demand.gputechconf.com/supercomputing/2012/presentation/SB006-Goodwin-
CUDA-Development-Nsight.pdf
 http://on-demand.gputechconf.com/gtc/2013/presentations/S3011-CUDA-Optimization-
With-Nsight-VSE.pdf