Conjugate gradient sparse solvers: performance-power characteristics

We characterize the performance and power attributes of the conjugate gradient (CG) sparse solver which is widely used in scientific applications. We use cycle-accurate simulations with SimpleScalar and Wattch, on a processor and memory architecture similar to the configuration of a node of the BlueGene/L. We first demonstrate that substantial power savings can be obtained without performance degradation if low power modes of caches can be utilized. We next show that if Dynamic Voltage Scaling (DVS) can be used, power and energy savings are possible, but these are realized only at the expense of performance penalties. We then consider two simple memory subsystem optimizations, namely memory and level-2 cache prefetching. We demonstrate that when DVS and low power modes of caches are used with these optimizations, performance can be improved significantly with reductions in power and energy. For example, execution time is reduced by 23%, power by 55% and energy by 65% in the final...

• Type: Conference
• Year: 2006
• Where: IPPS
• Authors: Konrad Malkowski, Ingyu Lee, Padma Raghavan, Mary Jane Irwin
• Keywords: Distributed And Parallel Computing, IPPS 2006, Low Power Modes, Performance, Substantial Power Savings