Efficient Scheduling of Nested Parallel Loops on Multi-Core Systems


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Parallel loops, such as a parallel DO loop, in Fortran, account for large percentage of the total execution time. Given this, we focus on the problem of how to efficiently schedule nested perfect/non-perfect parallel loops on the emerging multi-core systems. In this regard, one of the key aspects is how to determine the profitability of parallel execution and how to efficiently capture the cache behavior as the cache subsystem is often the main performance bottleneck in multi-core systems. In this paper, we present a novel profile-guided compiler technique for cache-aware scheduling of iteration spaces of such loops. Specifically, we propose a technique for iteration space scheduling which captures the effect of variation in the number of cache misses across the iteration space. Subsequently, we propose a general approach to capture the variation of both the number of cache misses and computation across the iteration space. We demonstrate the efficacy of our approach on a dedicated 4-way Intel Xeon based multiprocessor using several kernels from the industry-standard benchmarks.
cache behavior,multi-core systems,cache subsystem,parallel loop,multi-core system,nested parallel loops,parallel execution,iteration space scheduling,compiler technique,cache-aware scheduling,iteration space,non-perfect parallel loop,efficient scheduling,parallel processing,indexes,data mining,load balancing,interference,load balance,scheduling,multithreading,band pass filters,profitability
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