Low-power amdahl-balanced blades for data intensive computing
Alexander S. Szalay, Gordon C. Bell, H. Howie Huang, Andreas Terzis, Alainna White · ACM SIGOPS Operating Systems Review · 2010
Enterprise and scientific data sets double every year, forcing similar growths in storage size and power consumption. As a consequence, current system architectures used to build data warehouses are about to hit a power consumption wall. In this paper we propose an alternative architecture comprising large number of so-called Amdahl blades that combine energy-efficient CPUs with solid state disks to increase sequential read I/O throughput by an order of magnitude while keeping power consumption constant. We also show that while keeping the total cost of ownership constant, Amdahl blades offer five times the throughput of a state-of-theart computing cluster for data-intensive applications. Finally, using the scaling laws originally postulated by Amdahl, we show that systems for data-intensive computing must maintain a balance between low power consumption and per-server throughput to optimize performance perWatt.