Challenges in CISE: TUNE: System Support for Memory-Friendly Programming

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9726370 Trivedi, Kishor Board, John A. Duke University Challenges in CISE: TUNE: System Support for Memory-Friendly Programming The pervasive use of multi-level memory hierarchies in microprocessor-based machines makes the performance of an application primarily determined by and extremely sensitive to its memory mapping, and requires memory-friendly programming: careful layout of data structures and restructuring of code to improve data locality. Techniques for improving memory system performance manifest themselves at various levels, from high-level algorithms and data structures, through compile-time analysis and restructuring of programs, to special architectural primitives that allow an application to better manage the memory hierarchy. The lack of automatic tools for improving data locality currently forces many application programmers to manually restructure their codes. Unfortunately, the sophisticated algorithms seen in modern scientific computing require equally sophisticated restructuring techniques. These techniques require expertise in computer architecture, burden the programmer with tedious machine-specific details unrelated to program correctness, and reduce the readability, maintainability, and portability of the restructured code. For all these reasons, manual restructuring of programs of any significant size is untenable, and some kind of system support is necessary. This project targets all aspects of this problem, from developing the relevant mathematical techniques for representing and manipulating data locality, through implementing interactive and automatic data locality management tools, to proposing innovative memory architectures for future-generation systems. The efficacy of the resulting system will be demonstrated using programs representative of modern scientific computations including divide-and-conquer scientific computations such as N-body solvers (e.g., fastmultipole) and many linear algebra kernels (e.g., Strassens's matrix multiplication algo rithm).