R3-DLA (Reduce, Reuse, Recycle): A More Efficient Approach to Decoupled Look-Ahead Architectures
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Modern societies have developed insatiable demands for more computation capabilities. Exploiting implicit parallelism to provide automatic performance improvement remains a central goal in engineering future general-purpose computing systems. One approach is to use a separate thread context to perform continuous look-ahead to improve the data and instruction supply to the main pipeline. Such a decoupled look-ahead (DLA) architecture can be quite effective in accelerating a broad range of applications in a relatively straightforward implementation. It also has broad design flexibility as the look-ahead agent need not be concerned with correctness constraints. In this paper, we explore a number of optimizations that make the look-ahead agent more efficient and yet extract more utility from it. With these optimizations, a DLA architecture can achieve an average speedup of 1.4 over a state-of-the-art microarchitecture for a broad set of benchmark suites, making it a powerful tool to enhance single-thread performance.
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