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Essential CUDA Optimization Techniques - Presented by Acceleware (Session 4 of 4)
Abstract:
Learn how to optimize your algorithms for NVIDIA GPUs. This informative tutorial will provide an overview of the key optimization strategies for compute, latency and memory bound problems. The session will include techniques for ensuring peak utilization of CUDA cores by choosing the optimal block size. For compute bound algorithms we will discuss how to improve branching efficiency, intrinsic functions and loop unrolling. For memory bound algorithms, optimal access patterns for global and shared memory will be presented. Cooperative groups will also be introduced as an additional optimization technique. This session will include code examples throughout and a programming demonstration highlighting the optimal global memory access pattern which is applicable to all GPU architectures. Printed copies of the material will be provided to all attendees for each session - collect all four!
 
Topics:
Programming Languages
Type:
Tutorial
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8982
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