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The emergence of big data analytics and the need for cost/energy efficient IT infrastructure motivate a new focus on data-centric designs. In this paper, we aim to better understand the design implications of data analytics systems by quantifying workload requirements and runtime dynamics. We examine four workloads representing big data analytics trends for(More)
Recent proposals using low-power processors and Flash-based storage can dramatically improve the energy-efficiency of compute and storage subsystems in data-centric computing. However, in a balanced system design, these changes call for matching improvement in the network subsystem as well. Conventional Ethernet-based networks are a potential(More)
Motivated by the challenges of scaling up memory capacity and fully exploiting the benefits of memory compression, we propose Buri, a hardware-based memory compression scheme, which simultaneously achieves cost efficiency, high performance, and ease of adoption. Buri combines (1) a self-contained, ready-to-adopt hardware compression module, which manages(More)
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