Offload Annotations - Bringing Heterogeneous Computing to Existing Libraries and Workloads

Offload Annotations - Bringing Heterogeneous Computing to Existing Libraries and Workloads

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Goals

7 of 20

7 of 20

Goals

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Offload Annotations - Bringing Heterogeneous Computing to Existing Libraries and Workloads

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  1. 1 Intro
  2. 2 Background: Hardware Commoditization
  3. 3 Background: CPUs vs. GPUs
  4. 4 Background: Data Science on the CPU
  5. 5 Trend: Data Science on the GPU
  6. 6 Trend: CPU Libraries vs. GPU Libraries
  7. 7 Goals
  8. 8 Annotator - Function Annotations
  9. 9 Step 1: Annotator - Allocation Annotations
  10. 10 Step 1: Annotator - Offload Split Type
  11. 11 End User
  12. 12 Step 3: Runtime - Offloading API
  13. 13 Step 3: Runtime - Splitting API
  14. 14 Step 3: Runtime - Scheduling Heuristics (optional)
  15. 15 Integration Experience
  16. 16 Evaluation: Summary
  17. 17 In-Depth Evaluation: Allocations
  18. 18 In-Depth Evaluation: Heuristics
  19. 19 In-Depth Evaluation: Splitting/Paging Datasets
  20. 20 Conclusion

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