Demystifying GPU microarchitecture through microbenchmarking

—Graphics processors (GPU) offer the promise of more than an order of magnitude speedup over conventional processors for certain non-graphics computations. Because the ften presented as a C-like abstraction (e.g., Nvidia’s CUDA), little is known about the characteristics of the GPU’s architecture beyond what the manufacturer has documented. This work develops a microbechmark suite and measures the CUDA-visible architectural characteristics of the Nvidia GT200 (GTX280) GPU. Various undisclosed characteristics of the processing elements and the memory hierarchies are measured. This analysis exposes undocumented features that impact program performance and correctness. These measurements can be useful for improving performance optimization, analysis, and modeling on this architecture and offer additional insight on the decisions made in developing this GPU.

• Type: Conference
• Year: 2010
• Where: ISPASS
• Authors: Henry Wong, Misel-Myrto Papadopoulou, Maryam Sadooghi-Alvandi, Andreas Moshovos
• Keywords: Certain Non-graphics Computations, GPU’s Architecture, ISPASS 2010, Software Engineering, Various Undisclosed Characteristics