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Can traditional programming bridge the ninja performance gap for parallel computing applications?

, , , , , , , and . Commun. ACM, 58 (5): 77-86 (2015)

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A compiler for exploiting nested parallelism in OpenMP programs., , , , , and . Parallel Computing, 31 (10-12): 960-983 (2005)Exploring the Use of Hyper-Threading Technology for Multimedia Applications with Intel® OpenMP* Compiler., , , , , and . IPDPS, page 36. IEEE Computer Society, (2003)Effect of Optimizations on Performance of OpenMP Programs., and . HiPC, volume 3296 of Lecture Notes in Computer Science, page 133-143. Springer, (2004)Lightweight lock-free synchronization methods for multithreading., , , , , , , and . ICS, page 361-371. ACM, (2006)A general approach for partitioning N-dimensional parallel nested loops with conditionals., , , , , , and . SPAA, page 49-58. ACM, (2006)Automatic Intra-Register Vectorization for the Intel? Architecture., , , and . International Journal of Parallel Programming, 30 (2): 65-98 (2002)Extracting Task-Level Parallelism, and . ACM Trans. Program. Lang. Syst., 17 (4): 600-634 (1995)Incorporating Intel MMX technology into a Java JIT compiler., , and . Scientific Programming, 7 (1): 167-184 (1999)Compiling C/C++ SIMD Extensions for Function and Loop Vectorizaion on Multicore-SIMD Processors., , , , , , , , and . IPDPS Workshops, page 2349-2358. IEEE Computer Society, (2012)Can traditional programming bridge the Ninja performance gap for parallel computing applications?, , , , , , , and . ISCA, page 440-451. IEEE Computer Society, (2012)