2002 · 58 citations · 10 references
EngineeringCompiler TechnologyComputer ArchitectureComputational ComplexityHardware SystemsSoftware AnalysisParallel ComputingCompilersDynamic CompilationProgramming LanguagesParallelizing CompilerCompiler SupportComputer EngineeringIntel ParagonComputer ScienceOptimizing CompilerTheory Of ComputingPhysical MemoryProgram AnalysisMany-core ArchitectureParallel ProgrammingLu Factorization
Many computational methods are currently limited by the size of physical memory, the latency of disk storage, and the difficulty of writing an efficient out-of-core version of the application. We are investigating a compiler-based approach to the above problem. In general, our compiler techniques attempt to choreograph I/O for an application based on high-level programmer annotations similar to Fortran D's DECOMPOSITION, ALIGN, and DISTRIBUTE statements. The central problem is to generate "deferred routines" which delay computations until all the data they require have been read into main memory. We present the results for two applications, LU factorization and red-black relaxation, on 1 to 32 nodes of an Intel Paragon after hand application of these compiler techniques.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
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Compiling Fortran D for MIMD distributed-memory machines
Seema Hiranandani, Ken Kennedy, Chau‐Wen Tseng · Communications of the ACM · 1992 · 440 citations · Full text
Tolerating latency through software-controlled data prefetching
Todd C. Mowry · 1994 · 223 citations