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pro vyhledávání: '"Strout, Michelle"'
Autor:
Strout, Michelle
I propose an applications-first approach for adjusting how parallel and distributed computing concepts are incorporated into curricula. By focusing on practical applications that leverage parallelism and distributed systems, this approach aims to mak
Externí odkaz:
http://arxiv.org/abs/2410.12116
Autor:
Strout, Michelle Mills, LaMielle, Alan, Carter, Larry, Ferrante, Jeanne, Kreaseck, Barbara, Olschanowsky, Catherine
Applications that manipulate sparse data structures contain memory reference patterns that are unknown at compile time due to indirect accesses such as A[B[i]]. To exploit parallelism and improve locality in such applications, prior work has develope
Externí odkaz:
http://hdl.handle.net/10150/615800
http://arizona.openrepository.com/arizona/handle/10150/615800
http://arizona.openrepository.com/arizona/handle/10150/615800
This paper presents a code generator for sparse tensor contraction computations. It leverages a mathematical representation of loop nest computations in the sparse polyhedral framework (SPF), which extends the polyhedral model to support non-affine c
Externí odkaz:
http://arxiv.org/abs/2208.11858
Sparse fusion is a compile-time loop transformation and runtime scheduling implemented as a domain-specific code generator. Sparse fusion generates efficient parallel code for the combination of two sparse matrix kernels where at least one of the ker
Externí odkaz:
http://arxiv.org/abs/2111.12238
Autor:
Strout, Michelle Mills
Publikováno v:
Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses
Thesis (Ph. D.)--University of California, San Diego, 2003.
Vita. Includes bibliographical references (leaves 178-190).
Vita. Includes bibliographical references (leaves 178-190).
Externí odkaz:
http://wwwlib.umi.com/cr/ucsd/fullcit?p3094622
Hierarchical matrix approximations have gained significant traction in the machine learning and scientific community as they exploit available low-rank structures in kernel methods to compress the kernel matrix. The resulting compressed matrix, HMatr
Externí odkaz:
http://arxiv.org/abs/1812.07152
Autor:
Mohammadi, Mahdi Soltan, Cheshmi, Kazem, Gopalakrishnan, Ganesh, Hall, Mary, Dehnavi, Maryam Mehri, Venkat, Anand, Yuki, Tomofumi, Strout, Michelle Mills
Analyzing array-based computations to determine data dependences is useful for many applications including automatic parallelization, race detection, computation and communication overlap, verification, and shape analysis. For sparse matrix codes, ar
Externí odkaz:
http://arxiv.org/abs/1807.10852
Autor:
Gaska, Benjamin James, Jothi, Neha, Mohammadi, Mahdi Soltan, Volk, Kat, Strout, Michelle Mills
Nested parallelism exists in scientific codes that are searching multi-dimensional spaces. However, implementations of nested parallelism often have overhead and load balance issues. The Orbital Analysis code we present exhibits a sparse search space
Externí odkaz:
http://arxiv.org/abs/1707.09668
Publikováno v:
in SC 2017, Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
Sympiler is a domain-specific code generator that optimizes sparse matrix computations by decoupling the symbolic analysis phase from the numerical manipulation stage in sparse codes. The computation patterns in sparse numerical methods are guided by
Externí odkaz:
http://arxiv.org/abs/1705.06575
Computer science enrollments have started to rise again, but the percentage of women undergraduates in computer science is still low. Some studies indicate this might be due to a lack of awareness of computer science at the high school level. We pres
Externí odkaz:
http://arxiv.org/abs/1406.2222