textWe present a methodology for exploiting shared-memory parallelism within matrix computations by expressing linear algebra algorithms as directed acyclic graphs. Our solution involves a separation of concerns that completely hides the exploitation of parallelism from the code that implements the linear algebra algorithms. This approach to the problem is fundamentally different since we also address the issue of programmability instead of strictly focusing on parallelization. Using the separation of concerns, we present a framework for analyzing and developing scheduling algorithms and heuristics for this problem domain. As such, we develop a theory and practice of scheduling concepts for matrix computations in this dissertation.Compu...
Task graphs or dependence graphs are used in runtime systems to schedule tasks for parallel executio...
In this paper, we survey algorithms that allocate a parallel program represented by an edge-weighted...
Two issues in linear algebra algorithms for multicomputers are addressed. First, how tounify paralle...
textWe present a methodology for exploiting shared-memory parallelism within matrix computations by ...
Algorithms are often parallelized based on data dependence analysis manually or by means of parallel...
In this article the authors develop some algorithms and tools for solving matrix problems on paralle...
Run-time compilation techniques have been shown effective for automating the parallelization of loop...
It is anticipated that in order to make effective use of many future high performance architectures,...
This paper presents a theoretical framework for the efficient scheduling of a class of parallel loop...
The aim of data and task parallel scheduling for dense linear algebra kernels is to minimize the pro...
The tremendous increase in the size and heterogeneity of supercomputers makes it very difficult to p...
With the emergence of thread-level parallelism as the primary means for continued improvement of per...
Parallelization is one of the major challenges for programmers. But parallelizing existing code is a...
Graphics processing units (GPUs) are used as accelerators for algorithms in which the same instructi...
Three related problems, among others, are faced when trying to execute an algorithm on a parallel ma...
Task graphs or dependence graphs are used in runtime systems to schedule tasks for parallel executio...
In this paper, we survey algorithms that allocate a parallel program represented by an edge-weighted...
Two issues in linear algebra algorithms for multicomputers are addressed. First, how tounify paralle...
textWe present a methodology for exploiting shared-memory parallelism within matrix computations by ...
Algorithms are often parallelized based on data dependence analysis manually or by means of parallel...
In this article the authors develop some algorithms and tools for solving matrix problems on paralle...
Run-time compilation techniques have been shown effective for automating the parallelization of loop...
It is anticipated that in order to make effective use of many future high performance architectures,...
This paper presents a theoretical framework for the efficient scheduling of a class of parallel loop...
The aim of data and task parallel scheduling for dense linear algebra kernels is to minimize the pro...
The tremendous increase in the size and heterogeneity of supercomputers makes it very difficult to p...
With the emergence of thread-level parallelism as the primary means for continued improvement of per...
Parallelization is one of the major challenges for programmers. But parallelizing existing code is a...
Graphics processing units (GPUs) are used as accelerators for algorithms in which the same instructi...
Three related problems, among others, are faced when trying to execute an algorithm on a parallel ma...
Task graphs or dependence graphs are used in runtime systems to schedule tasks for parallel executio...
In this paper, we survey algorithms that allocate a parallel program represented by an edge-weighted...
Two issues in linear algebra algorithms for multicomputers are addressed. First, how tounify paralle...