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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 a novel alternative architecture comprising large number of so-called Amdahl blades that combine energyefficient 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-the-art computing cluster for data-intensive applications. Finally, using the scaling laws originally postulated by Amdahl, we show that systems for dataintensive computing must maintain a balance between low power consumption and per-server throughput to optimize performance per Watt.

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