کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10358594 | 868543 | 2014 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Fine-grained bulge-chasing kernels for strongly scalable parallel QR algorithms
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
The bulge-chasing kernel in the small-bulge multi-shift QR algorithm for the non-symmetric dense eigenvalue problem becomes a sequential bottleneck when the QR algorithm is run in parallel on a multicore platform with shared memory. The duration of each kernel invocation is short, but the critical path of the QR algorithm contains a long sequence of calls to the bulge-chasing kernel. We study the problem of parallelizing the bulge-chasing kernel itself across a handful of processor cores in order to reduce the execution time of the critical path. We propose and evaluate a sequence of four algorithms with varying degrees of complexity and verify that a pipelined algorithm with a slowly shifting block column distribution of the Hessenberg matrix is superior. The load-balancing problem is non-trivial and computational experiments show that the load-balancing scheme has a large impact on the overall performance. We propose two heuristics for the load-balancing problem and also an effective optimization method based on local search. Numerical experiments show that speed-ups are obtained for problems as small as 40Â ÃÂ 40 on two different multicore architectures.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Parallel Computing - Volume 40, Issue 7, July 2014, Pages 271-288
Journal: Parallel Computing - Volume 40, Issue 7, July 2014, Pages 271-288
نویسندگان
L. Karlsson, B. KÃ¥gström, E. Wadbro,