Automatic Measurement of Instruction Cache Capacity

There is growing interest in autonomic computing systems that can optimize their own behavior on different platforms without manual intervention. Examples of successful self-optimizing systems are ATLAS, which generates Basic Linear Algebra Subroutine (BLAS) Libraries, and FFTW, which generates FFT libraries. Self-optimizing systems may need the values of hardware parameters such as the number of registers of various types and the capacities of caches at various levels. For example, ATLAS uses the capacity of the L1 cache and the number of registers in determining the size of cache tiles and register tiles. We have built a system called X-Ray1 , which uses micro-benchmarks to measure such parameter values automatically. The micro-benchmarks currently implemented in X-Ray can determine the latency of various instructions, the existence of important instructions like fused multiplyadd, the number of registers of various kinds, and parameters of the memory hierarchy. In this paper, we d...

• Type: Conference
• Year: 2005
• Where: LCPC
• Authors: Kamen Yotov, Sandra Jackson, Tyler Steele, Keshav Pingali, Paul Stodghill
• Keywords: Autonomic Computing Systems, Basic Linear Algebra, LCPC 2005, Self-optimizing Systems