Identifying energy-efficient concurrency levels using machine learning

Abstract-- Multicore microprocessors have been largely motivated by the diminishing returns in performance and the increased power consumption of single-threaded ILP microprocessors. With the industry already shifting from multicore to many-core microprocessors, software developers must extract more thread-level parallelism from applications. Unfortunately, low power-efficiency and diminishing returns in performance remain major obstacles with many cores. Poor interaction between software and hardware, and bottlenecks in shared hardware structures often prevent scaling to many cores, even in applications where a high degree of parallelism is potentially available. In some cases, throwing additional cores at a problem may actually harm performance and increase power consumption. Better use of otherwise limitedly beneficial cores by software components such as hypervisors and operating systems can improve system-wide performance and reliability, even in cases where power consumption is n...

• Type: Conference
• Year: 2007
• Where: CLUSTER
• Authors: Matthew Curtis-Maury, Karan Singh, Sally A. McKee, Filip Blagojevic, Dimitrios S. Nikolopoulos, Bronis R. de Supinski, Martin Schulz
• Keywords: CLUSTER 2007, Diminishing Returns, Distributed And Parallel Computing, Power Consumption, Single-threaded Ilp Microprocessors