AI Summary & Key Takeaways
AI InsightAccording to our estimates, the total processor power is reduced by 12%, on the average.
📌 3 Key Takeaways
Abstract
Nowadays, all the designers of systems from high-performance servers to battery-operated handheld devices aim for reliability, high-performance and longevity. Central within these aims the issue of processor power consumption is becoming increasingly important. In this study, we aim to adapt our already-proven method for single-threaded superscalar processors to simultaneous multi-threaded (SMT) processors for energy savings. The original method focused on resizing datapath resources according to the demands of running applications. To achieve this, the targeted resources are physically divided into multiple partitions, and turned on and off according to the needs of the applications. Since, the energy consumption of the turned-off datapath resources is quite low, as a result, it becomes possible to have great amount of energy savings within a processor. However, special care must be taken when there are multiple threads racing against each other to gain access to shared datapath resources. As a result, our proposed microarchitectural technique achieves 0.5% Instructions Per Cycle (IPC) and 3.2% Total number of instructions Per Cycle (TPC) improvement, while it turns off 45% of the Reorder Buffer (ROB), 59% of the Load-Store Queue (LSQ), 43% of the Issue Queue (IQ), 30% of the integer Physical Register Files (PRF) and, finally, 48% of the floating PRF, on the average across all simulated benchmarks. According to our estimates, the total processor power is reduced by 12%, on the average.
Özet
Nowadays, all the designers of systems from high-performance servers to battery-operated handheld devices aim for reliability, high-performance and longevity. Central within these aims the issue of processor power consumption is becoming increasingly important. In this study, we aim to adapt our already-proven method for single-threaded superscalar processors to simultaneous multi-threaded (SMT) processors for energy savings. The original method focused on resizing datapath resources according to the demands of running applications. To achieve this, the targeted resources are physically divided into multiple partitions, and turned on and off according to the needs of the applications. Since, the energy consumption of the turned-off datapath resources is quite low, as a result, it becomes possible to have great amount of energy savings within a processor. However, special care must be taken when there are multiple threads racing against each other to gain access to shared datapath resources. As a result, our proposed microarchitectural technique achieves 0.5% Instructions Per Cycle (IPC) and 3.2% Total number of instructions Per Cycle (TPC) improvement, while it turns off 45% of the Reorder Buffer (ROB), 59% of the Load-Store Queue (LSQ), 43% of the Issue Queue (IQ), 30% of the integer Physical Register Files (PRF) and, finally, 48% of the floating PRF, on the average across all simulated benchmarks. According to our estimates, the total processor power is reduced by 12%, on the average.