International audienceThe multicore revolution is underway. Classical algorithms must be revisited in order to take the hierarchical memory layout into account. In this paper, we aim at minimizing the number of cache misses paid during the execution of the matrix product kernel on a multicore processor, and we show how to achieve the best possible tradeoff between shared and distributed caches. Comprehensive simulation results confirm the analytical performance predictions and fully establish the practical significance of our new algorithms
AbstractIn this article, we present a fast algorithm for matrix multiplication optimized for recent ...
Abstract-- In this work, the performance of basic and strassen’s matrix multiplication algorithms ar...
During the last half-decade, a number of research efforts have centered around developing software f...
International audienceThe multicore revolution is underway. Classical algorithms must be revisited i...
nombre de pages: 25The multicore revolution is underway, bringing new chips introducing more complex...
The multicore revolution is underway. Classical algorithms have to be revisited in order to take hie...
The multicore revolution is underway. Classi-cal algorithms have to be revisited in order to take hi...
The multicore revolution is underway, bringing new chips introducing more complex memory architectur...
In previous work, a cache-aware sparse matrix multiplication for linear programming interior point m...
This report deals with the ecient calculation of matrix-matrix multiplication, without using explici...
In modern clustering environments where the memory hierarchy has many layers (distributed memory, sh...
This Master Thesis examines if a matrix multiplication program that combines the two efficiency stra...
International audienceIn this paper, a new methodology for computing the Dense Matrix Vector Multipl...
Out-of-core implementations of algorithms for dense matrix computations have traditionally focused o...
As computation processing capabilities have outstripped memory transport speeds, memory management c...
AbstractIn this article, we present a fast algorithm for matrix multiplication optimized for recent ...
Abstract-- In this work, the performance of basic and strassen’s matrix multiplication algorithms ar...
During the last half-decade, a number of research efforts have centered around developing software f...
International audienceThe multicore revolution is underway. Classical algorithms must be revisited i...
nombre de pages: 25The multicore revolution is underway, bringing new chips introducing more complex...
The multicore revolution is underway. Classical algorithms have to be revisited in order to take hie...
The multicore revolution is underway. Classi-cal algorithms have to be revisited in order to take hi...
The multicore revolution is underway, bringing new chips introducing more complex memory architectur...
In previous work, a cache-aware sparse matrix multiplication for linear programming interior point m...
This report deals with the ecient calculation of matrix-matrix multiplication, without using explici...
In modern clustering environments where the memory hierarchy has many layers (distributed memory, sh...
This Master Thesis examines if a matrix multiplication program that combines the two efficiency stra...
International audienceIn this paper, a new methodology for computing the Dense Matrix Vector Multipl...
Out-of-core implementations of algorithms for dense matrix computations have traditionally focused o...
As computation processing capabilities have outstripped memory transport speeds, memory management c...
AbstractIn this article, we present a fast algorithm for matrix multiplication optimized for recent ...
Abstract-- In this work, the performance of basic and strassen’s matrix multiplication algorithms ar...
During the last half-decade, a number of research efforts have centered around developing software f...