Debugging CUDA applications
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Looking at major application development challenges and solutions for debugging CUDA applications. A short presentation on the latest feature set.
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Speaker: Robbie King
Date: September 17, 2014
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★ Session Summary ★
Cisco to present their experience using ODP to provide portable accelerated access to crypto functions on various SoCs.
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★ Event Details ★
Linaro Connect USA - #LCU14
September 15-19th, 2014
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The core solution presented is defining domain-specific languages (DSLs) that model business rules as data structures rather than imperative code. This approach offers three key benefits:
1. Constraining what operations are possible
2. Keeping documentation aligned with code through automatic generation
3. Making solutions consistent throug different interpreters
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Debugging CUDA applications
- 1. 1© 2017 Rogue Wave Software, Inc. All Rights Reserved. 1 Debugging CUDA applications GPU Technology Conference Roundtable discussions
- 2. 2© 2017 Rogue Wave Software, Inc. All Rights Reserved. 2 Complexity in debugging CUDA • Heavily parallel – Explosion in threads – Usage of MPI, OpenMP, OpenACC • Used together • Complex platforms – CPUs with GPUs many times mixed • Multiple languages being used – Python for ease of use – C/C++ for speed and legacy algorithms – The data passing and glue code adds complexity
- 3. 3© 2017 Rogue Wave Software, Inc. All Rights Reserved. 3 Directive languages + GPUs debugging • OpenMP 4 debugging support (CPUs and GPUs) for Sierra • Collaborate on OpenMP Debug API (OMPD) design • Three phases – Phase 1: OMPD: OMP3.1/CPU, x86_64 – Phase 2: OMPD: OMP4/CPU/GPU, x86_64 – Phase 3: OMPD: OMP4/CPU/GPU, PowerLE – Need compiler support to make it all work – OpenACC works always interested in user input
- 4. 4© 2017 Rogue Wave Software, Inc. All Rights Reserved. 4 Current debugging advancements Debugging multiple processes needs to be exclusive Support one debug process per GPU
- 5. 5© 2017 Rogue Wave Software, Inc. All Rights Reserved. 5 Python with filtering Python code available by choosing the stack frame Program counter shows where the call was made from in Python Come on Thursday to S7506 - ROLLING IN THE DEEP for details
- 6. 6© 2017 Rogue Wave Software, Inc. All Rights Reserved. 6 TotalView for the NVIDIA ® GPU Accelerator • TotalView – Leading debugger for multi- threaded issues at scale • CUDA 8.0 • Cray, OpenPOWER, Linux, OpenACC • Compiler: GCC, PGI • Features and capabilities include – MPI-based clusters – Flexible Display and Navigation – Memory address spaces – Leverages CUDA memcheck – CUDA dynamic parallelism © 2015 ROGUE WAVE SOFTWARE, INC. ALL RIGHTS RESERVED
- 7. 7© 2017 Rogue Wave Software, Inc. All Rights Reserved. 7 Interested in learning more about TotalView for HPC: www.roguewave.com
- 8. 8© 2017 Rogue Wave Software, Inc. All Rights Reserved. 8
- 9. 9© 2017 Rogue Wave Software, Inc. All Rights Reserved. 9 TotalView for HPC • Comprehensive multi-threaded analysis and debug environment – Thread specific breakpoints – Control individual thread execution – View thread specific stack and data – View complex data types easily • Integrated Reverse debugging • Track memory leaks in running applications • Supports C/C++ on Linux • Allowing the business to have – Predictable development schedules – Less time spent debugging
Editor's Notes
- #7: CLG: Added slide