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Heterogeneous computing
- 2. INTRODUCTION Heterogeneous computing refers to systems that use more than one kind of processor or cores. System gain performance with dissimilar coprocessors. Source:- Qualcomm Snapdragon
- 4. ISSUES WITH LEGACY GPU COMPUTE • Multiple memory pools • Multiple address spaces • Expert programmers only Source:-AMD
- 5. • Two memory pools remain • Still queue through the OS • Still requires expert programmers Source:-AMD Physical Integration
- 6. Heterogeneous System Architecture It allows integration of central processing units and graphics processors on the same bus, with shared memory and tasks. HSA is being developed by HSA Foundation. Aim to reduce communication latency between CPUs, GPUs and other compute devices, and make devices more compatible from a programmer’s perspective.
- 7. • Unified Coherent Memory enables data sharing across all processors • Processors architected to operate cooperatively • Designed to enable the application to run on different processors at different times This is HSA Source:-AMD
- 8. Source:-AMD
- 9. Source:-AMD
- 11. Source:-AMD
- 12. Programming for HSA 1. OpenCL 2. CUDA 3. hUMA
- 13. OpenCL • OpenCL initially developed by Apple Inc. • OpenCL is a framework for writing programs that execute across heterogenous platforms • Allows existing source code to target the CPU and GPU. CUDA • CUDA is a parallel computing platform and application programming interface model created by Nvidia. • It contains libraries,Compiler directives ,c,c++, and Fortran extensions • Free but limited to only Nvidia hardware hUMA • hUMA stands for Heterogeneous Uniform Memory Access • Results in support for mainstream languages such as Python, C++ and Java
- 14. Example Platforms Samsung Exynos Apple “A” series AMD APUs ARM big.LITTLE CPU architecture
- 15. Real World Application of HC AMD APUs Smartphones Laptops PlayStation 3 and PlayStation 4 Xbox One
- 16. Pros Small and efficient processor Better battery life Lower cost Increased performance for parallel applications
- 17. Cons A discrete CPU and GPU can provide more power New software design models
- 18. References 1. Shan, Amar (2006). Heterogeneous Processing: a Strategy for Augmenting Moore's Law. Linux Journal. 2. A Survey Of Techniques for Architecting and Managing Asymmetric Multicore Processors, ACM Computing Surveys, 2015. 3. AMD 4. Wikipedia
- 19. THANK YOU