Cudadma: Overview and Code Examples

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Motivation 2: Performance Bottlenecks Memory System Bottlenecks Instruction Issue Memory Level Parallelism (MLP) Data Access Patterns Coalescing Computational Bottlenecks � Long-latency memory accesses � Synchronization overheads � Data Access Patterns � Control Divergence Goal: remove bottlenecks <strong>and</strong> entanglement
Warp Specialization CudaDMA enables warp specialization: DMA warps Maximize MLP Compute warps No stalls due to memory CudaDMA objects manage warp specialization Describe data transfer patterns Independent of warp count
Page 1 and 2: CudaDMA: Overview and Code Examples
Page 3 and 4: Outline Motivation CudaDMA API Code
Page 5: // update the data slice in smem s_
Page 9 and 10: CudaDMA API Declare CudaDMA object
Page 11 and 12: CudaDMA App Structure: Warp Special
Page 13 and 14: Buffering Techniques Usually one se
Page 15 and 16: CudaDMA Instances CudaDMASequential
Page 17 and 18: Code Example: SAXPY Baseline: Typic
Page 19 and 20: Code Example: SGEMV (with warp spec
Page 21 and 22: A few experimental results…
Page 23 and 24: 3D Finite-Difference Stencil Use DM
Page 25 and 26: Thank You! http://code.google.com/p
Page 27: Warp Defintion Each CTA is decompos

Cudadma: Overview and Code Examples

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