In this paper we study the impact of the simultaneous exploitation of data-- and task--parallelism on Strassen and Winograd matrix multiplication algorithms. We present two mixed--parallel implementations. The former follows the phases of the original algorithms while the latter has been designed as the result of a list scheduling algorithm. We give a theoretical comparison- , in terms of memory usage and execution time, between our algorithms and classical data--parallel implementations. This analysis is corroborated by experiments. Finally we give some hints about an heterogeneous version of our algorithms
This paper examines how to write code to gain high performance on modern computers as well as the im...
Today current era of scientific computing and computational theory involves high exhaustive data com...
Strassen's algorithm for matrix multiplication gains its lower arithmetic complexityatthe expe...
In this paper we study the impact of the simultaneous exploitation of data- and task-parallelism, so...
The paper presents analysis of matrix multiplication algorithms from the point of view of their effi...
Abstract: Strassen’s algorithm to multiply two n×n matrices reduces the asymptotic operation count f...
International audienceWe propose several new schedules for Strassen-Winograd's matrix multiplication...
[[abstract]]We present a parallel method for matrix multiplication on distributed-memory MIMD archit...
We present a parallel method for matrix multiplication on distributedmemory MIMD architectures based...
AbstractWe present a parallel method for matrix multiplication on distributed-memory MIMD architectu...
Parallel matrix multiplication is one of the most studied fun-damental problems in distributed and h...
Matrix multiplication is one of the important operations in scientific and engineering application. ...
Many fast algorithms in arithmetic complexity have hierarchical or recursive structures that make ef...
Parallel matrix multiplication is one of the most studied fun-damental problems in distributed and h...
Parallel computing on networks of workstations are intensively used in some application areas such a...
This paper examines how to write code to gain high performance on modern computers as well as the im...
Today current era of scientific computing and computational theory involves high exhaustive data com...
Strassen's algorithm for matrix multiplication gains its lower arithmetic complexityatthe expe...
In this paper we study the impact of the simultaneous exploitation of data- and task-parallelism, so...
The paper presents analysis of matrix multiplication algorithms from the point of view of their effi...
Abstract: Strassen’s algorithm to multiply two n×n matrices reduces the asymptotic operation count f...
International audienceWe propose several new schedules for Strassen-Winograd's matrix multiplication...
[[abstract]]We present a parallel method for matrix multiplication on distributed-memory MIMD archit...
We present a parallel method for matrix multiplication on distributedmemory MIMD architectures based...
AbstractWe present a parallel method for matrix multiplication on distributed-memory MIMD architectu...
Parallel matrix multiplication is one of the most studied fun-damental problems in distributed and h...
Matrix multiplication is one of the important operations in scientific and engineering application. ...
Many fast algorithms in arithmetic complexity have hierarchical or recursive structures that make ef...
Parallel matrix multiplication is one of the most studied fun-damental problems in distributed and h...
Parallel computing on networks of workstations are intensively used in some application areas such a...
This paper examines how to write code to gain high performance on modern computers as well as the im...
Today current era of scientific computing and computational theory involves high exhaustive data com...
Strassen's algorithm for matrix multiplication gains its lower arithmetic complexityatthe expe...