Irregular reductions form the core of adaptive irregular codes. On distributed-memory multiprocessors, they are parallelized either using sophisticated run-time systems (e.g., CHAOS, PILAR) or the shared-memory interface supported by software DSMs (e.g., CVM, TreadMarks). We introduce LOCALWRITE, a new technique based on the owner-computes rule which eliminates the need for buffers or synchronized writes but may replicate computation. We evaluate its performance for irregular codes while

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... connectivity, locality, and adaptivity. LOCALWRITE improves performance by 50-150% compared to using replicated buffers, and can match or exceed gather/scatter for applications with low locality or high adaptivity.