Evaluating the locality benefits of active messages

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Abstract
A major challenge in fine-grained computing is achieving locality without excessive scheduling overhead. We built two J-Machine implementations of a fine-grained programming model, the Berkeley Threaded Abstract Machine. One implementation takes an Active Messages approach, maintaining a scheduling hierarchy in software in order to improve data cache performance. Another approach relies on the J-Machine's message queues and fast task switch, lowering the control costs at the expense of data locality. Our analysis measures the costs and benefits of each approach, for a variety of programs and cache configurations. The Active Messages implementation is strongest when miss penalties are high and for the finest-grained programs. The hardware-buffered implementation is strongest in direct-mapped caches, where it achieves substantially better instruction cache performance.

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