GPU Architectures - courses.cs.washington.edu

5/21/2013 1 GPU Architectures A CPU Perspective D e r e k H o we r A M D Re s e a r c h 5 / 2 1 / 2 0 1 3 Goals Data Parallelism: What is it, and how to exploit it? Workload characteristics Execution Models / GPU Architectures MIMD (SPMD), SIMD, SIMT GPU Programming Models Terminology translations: CPU AMD GPU Nvidia GPU Intro to OpenCL Modern GPU Microarchitectures , programmable GPU pipelines, not their fixed-function predecessors Advanced Topics: (Time permitting) The Limits of GPUs: What they can and cannot do The Future of GPUs: Where do we go from here? 2 GPU Architectures : A CPU PERSPECTIVE 5/21/2013 2 Data Parallel Execution on GPUs D a t a Pa ra l l e l i s m , P ro g ra m m i n g M o d e l s , S I M T 3 GPU Architectures : A CPU PERSPECTIVE Graphics Workloads Streaming computation GPU 4 GPU Architectures : A CPU PERSPECTIVE 5/21/2013 3 Graphics Workloads Streaming computation on pixels GPU 5 GPU Architectures : A CPU

Multicore Multithreaded SIMT Many SIMT “threads” grouped together into GPU “Core” SIMT threads in a group ≈ SMT threads in a CPU core Unlike CPU, groups are exposed to programmers Multiple GPU “Cores” GPU ARCHITECTURES: A CPU PERSPECTIVE 23 GPU “Core” GPU “Core” GPU This is a GPU Architecture (Whew!)

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