Analytical Modeling Is Enough for High-Performance BLIS

DOI10.1145/2925987zbMath1369.65200OpenAlexW2516525699WikidataQ113310172 ScholiaQ113310172MaRDI QIDQ5270773

Tze Meng Low, Tyler M. Smith, Enrique S. Quintana-Ortí, Francisco D. Igual

Publication date: 30 June 2017

Published in: ACM Transactions on Mathematical Software (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10234/163618

zbMATH Keywords

high performancelinear algebramatrix multiplicationanalytical modelinglibraries

Mathematics Subject Classification ID

Packaged methods for numerical algorithms (65Y15) Numerical linear algebra (65Fxx)

Related Items (4)

Analytical modeling of matrix–vector multiplication on multicore processors ⋮ Optimized implementation for calculation and fast-update of Pfaffians installed to the open-source fermionic variational solver mVMC ⋮ Implementing High-Performance Complex Matrix Multiplication via the 1M Method ⋮ Strassen's Algorithm for Tensor Contraction

Uses Software

• ATLAS
• LAPACK
• BLAS
• PHiPAC
• BLIS
• MKL
• OpenBLAS
• GotoBLAS
• BLIS
• AUGEM

Cites Work

• Unnamed Item
• BLIS: A Framework for Rapidly Instantiating BLAS Functionality
• A systematic approach to classify design-time global scheduling techniques
• Anatomy of high-performance matrix multiplication
• An extended set of FORTRAN basic linear algebra subprograms
• LAPACK Users' Guide
• Basic Linear Algebra Subprograms for Fortran Usage
• A set of level 3 basic linear algebra subprograms
• Codesign Tradeoffs for High-Performance, Low-Power Linear Algebra Architectures
• Automated empirical optimizations of software and the ATLAS project

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