Tuning memory performance of sequential and parallel programs

To improve program memory performance, programmers and compiler writers can transform the application so that its memory-referencing behavior better exploits the memory hierarchy. The challenge in achieving these program transformations is overcoming the difficulty of statically analyzing or reasoning about an application´s referencing behavior and interactions. In addition, many performance-monitoring tools collect high-level information that is inadequately detailed to analyze specific memory performance bugs. We describe MemSpy, a performance-monitoring tool we designed to help programmers discern where and why memory bottlenecks occur. MemSpy guides programmers toward program transformations that improve memory performance through detailed statistics on cache-miss causes and frequency. Because of the natural link between data-reference patterns and memory performance, MemSpy helps programmers comprehend data structure and code segment interactions by displaying statistics in terms of both the program´s data and code structures, rather than for code structures alone