This paper presents CRISP, the first runtime analytical model of performance in the face of changing frequency in a GPGPU. It shows that prior models not targeted at a GPGPU fail to account for important characteristics of GPGPU execution, including the high degree of overlap between memory access and computation and the frequency of store-related stalls. CRISP provides significantly greater accuracy than prior runtime performance models, being within 4% on average when scaling frequency by up to 7X. Using CRISP to drive a runtime energy efficiency controller yields a 10.7% improvement in energy-delay product, vs 6.2% attainable via the best prior performance model.
Nath et al. REF present CRISP model which analyze the performance in the face of different frequencies of compute cores.
The CRISP performance model for dynamic voltage and frequency scaling in a GPGPU
MICRO-48
Computer Science