AbstractIn this paper we construct an analytic model of cache misses during matrix multiplication. The analysis in this paper applies to square matrices of size 2m where the array layout function is given in terms of a function Θ that interleaves the bits in the binary expansions of the row and column indices. We first analyze the number of cache misses for direct-mapped caches and then indicate how to extend this analysis to A-way associative caches. The work in this paper accomplishes two things. First, we construct fast algorithms to estimate the number of cache misses. Second, we develop a theoretical understanding of cache misses that will allow us, in subsequent work, to approach the problem of minimizing cache misses by appropriately...
This report deals with the ecient calculation of matrix-matrix multiplication, without using explici...
. Many scientific applications handle compressed sparse matrices. Cache behavior during the executio...
AbstractOne of the keys to tap the full performance potential of current hardware is the optimal uti...
In this paper we construct an analytic model of cache misses during matrix multiplication. The analy...
AbstractIn this paper we construct an analytic model of cache misses during matrix multiplication. T...
As computation processing capabilities have outstripped memory transport speeds, memory management c...
Abstract-- In this work, the performance of basic and strassen’s matrix multiplication algorithms ar...
In this thesis we introduce a cost measure to compare the cache- friendliness of different permutati...
Algorithms for the sparse matrix-vector multiplication (shortly SpMxV) are important building blocks...
Sparse matrices are in the kernel of numerical applications. Their compressed storage, which permits...
Blocking is a well-known optimization technique for improving the effectiveness of memory hierarchie...
Cache behavior is complex and inherently unstable, yet it is a critical factor affecting program per...
We consider the problem of building high-performance implementations of sparse matrix-vector multipl...
Abstract. We present new performance models and more compact data structures for cache blocking when...
We present new performance models and a new, more compact data structure for cache blocking when ap...
This report deals with the ecient calculation of matrix-matrix multiplication, without using explici...
. Many scientific applications handle compressed sparse matrices. Cache behavior during the executio...
AbstractOne of the keys to tap the full performance potential of current hardware is the optimal uti...
In this paper we construct an analytic model of cache misses during matrix multiplication. The analy...
AbstractIn this paper we construct an analytic model of cache misses during matrix multiplication. T...
As computation processing capabilities have outstripped memory transport speeds, memory management c...
Abstract-- In this work, the performance of basic and strassen’s matrix multiplication algorithms ar...
In this thesis we introduce a cost measure to compare the cache- friendliness of different permutati...
Algorithms for the sparse matrix-vector multiplication (shortly SpMxV) are important building blocks...
Sparse matrices are in the kernel of numerical applications. Their compressed storage, which permits...
Blocking is a well-known optimization technique for improving the effectiveness of memory hierarchie...
Cache behavior is complex and inherently unstable, yet it is a critical factor affecting program per...
We consider the problem of building high-performance implementations of sparse matrix-vector multipl...
Abstract. We present new performance models and more compact data structures for cache blocking when...
We present new performance models and a new, more compact data structure for cache blocking when ap...
This report deals with the ecient calculation of matrix-matrix multiplication, without using explici...
. Many scientific applications handle compressed sparse matrices. Cache behavior during the executio...
AbstractOne of the keys to tap the full performance potential of current hardware is the optimal uti...