APEX

摘要

Memory accesses represent a major bottleneck in embedded systems power and performance. Traditionally, designers tried to alleviate this problem by relying on a simple cache hierarchy, or a limited use of special purpose memory modules such as stream buffers. Although real-life applications contain a large number of memory references to a diverse set of data structures, a significant percentage of all memory accesses in the application are generated from a few memory instructions that exhibit predictable, well-known access patterns; this creates an opportunity for memory customization, targeting the needs of these access patterns. We present APEX, an approach that extracts, analyzes and clusters the most active access patterns in the application, and aggressively customizes the memory architecture to match the needs of the application, exploring a wide range of cost, performance and power designs. We use a heuristic to prune the design space, guiding the exploration towards the best cost/gain ratios. We present experiments on a set of large real-life benchmarks, showing significant performance improvements for varied cost and power characteristics, allowing the designer to best target the system goals.