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Evaluating the Imagine Stream Processor. Jung Ho Ahn , William J. Dally, Brucek Khailany , Ujval J. Kapasi , and Abhishek Das ISCA 2004. Motivation. Provide efficiency of an ASIC Provide flexibility of a programmable processor Simplify special-purpose processor design
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Evaluating the Imagine Stream Processor Jung Ho Ahn, William J. Dally, BrucekKhailany, Ujval J. Kapasi, and Abhishek Das ISCA 2004
Motivation • Provide efficiency of an ASIC • Provide flexibility of a programmable processor • Simplify special-purpose processor design • Lower special-purpose processor design cost • Provide better applicability • Target media applications
Development Board PowerPC, 150 MHz 2 x Imagine, 200 MHz FPGA Bridge, 66 MHz 256MB of SDRAM / Imagine, 100 MHz
Execution on a Single Stream Kernel 1 SRF Iteration 1 … Input Stream … … Output Stream … Iteration n … … …
Execution of Multiple Kernels Kernel 1 SRF Stream 1 … processing… … … Stream 2 Kernel 2 … … Stream 3 processing… … … Kernel 3 Stream 4 … … processing… …
Application Performance GOPS: 18% GFLOPS: 60%
Energy Efficiency Energy consumption per FLOP : (when normalized to 0.13um 1.2V process) Imagine @ 200 MHz: 277pJ/FLOP TI C67x DSP @ 225MHz: 889pJ/FLOP (3.2x more) Intel Pentium M @ 1200GHz: 3600pJ/FLOP (13x more)
Compiler OptimizationsLoop Unrolling and Software Pipelining
Conclusions • Provides performance close to that of ASIC and flexibility via programming • Can sustain between 16% and 60% of the peak arithmetic performance • Exposed 2-level register file allows compiler to exploit locality • Broader applicability • Requires considerable programming effort • Limited to media applications with regular control-flow
Collab Questions • How does the performance compare to other processors? (Dan, Marko, Jason, Prateeksha, Chris) • What is the compiler efficiency? (Mario, Liang) • How were the design decisions motivated? (Jing, Marisabel) • How does the programming model compare to that of GPUs? (Greg)