scholarly journals Memory efficient scheduling of Strassen-Winograd's matrix multiplication algorithm

2009 ◽  
Author(s):  
Brice Boyer ◽  
Jean-Guillaume Dumas ◽  
Clément Pernet ◽  
Wei Zhou
Keyword(s):  
Matrix Multiplication ◽  
Matrix Multiplication Algorithm ◽  
Multiplication Algorithm ◽  
Memory Efficient

EXPERIMENTAL EVALUATION OF BSP PROGRAMMING LIBRARIES

2008 ◽  
Vol 18 (01) ◽  
pp. 7-21 ◽  
Author(s):  
PETER KRUSCHE
Keyword(s):  
Parallel Computation ◽  
Experimental Evaluation ◽  
Matrix Multiplication ◽  
Parallel Computers ◽  
General Purpose ◽  
Matrix Multiplication Algorithm ◽  
Bulk Synchronous Parallel ◽  
Multiplication Algorithm ◽  
Theoretical Results ◽  
Memory Efficient

The model of bulk-synchronous parallel computation (BSP) helps to implement portable general purpose algorithms while maintaining predictable performance on different parallel computers. Nevertheless, when programming in ‘BSP style’, the running time of the implementation of an algorithm can be very dependent on the underlying communication library. In this study, an overview of existing approaches to practical BSP programming in C/C++ or Fortran is given and benchmarks were run for the two main BSP-like communication libraries, the Oxford BSP Toolset and PUB. Furthermore, a memory efficient matrix multiplication algorithm was implemented and used to compare their performance on different parallel computers and to evaluate the compliance with predictions by theoretical results.

scholarly journals Autotuning LLVM OptimizationPasses for Matrix Multiplication in Rust

2020 ◽  
Author(s):  
Emanuel Lima de Sousa ◽  
Pedro Bruel ◽  
Alfredo Goldman
Keyword(s):  
Execution Time ◽  
Expert Knowledge ◽  
Matrix Multiplication ◽  
Intermediate Representation ◽  
Matrix Multiplication Algorithm ◽  
Search Spaces ◽  
Multiplication Algorithm ◽  
Ongoing Work ◽  
Compiler Framework

The LLVM compiler framework transforms its Intermediate Representation (IR) to optimize code. These transformations are controlled by flags which interfere on metrics such as the execution time. Selecting flags to improve the execution time of a program is difficult, and requires expert knowledge. Autotuning methods can automate parts of this process and help understanding the underlying search spaces. This paper describes ongoing work, showing that LLVM flags can impact the execution time of a Rust matrix multiplication algorithm, and planning future autotuning experiments for flag selection.

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