A parallel file may be physically stored on several independent disks and logically partitioned by several processors. This paper presents general algorithms for mapping between two arbitrary distributions of a parallel file. Each of the two distributions may be physical or logical. The algorithms are optimized for multidimensional array partitions. We motivate our approach and present potential utilizations. We compare and contrast with related work. The paper also presents a study case, the employment of mapping functions and redistribution algorithms in a parallel file system
We consider distribution at compile time of the array data in a distributed-memory implementation of...
Parallel architectures with physically distributed memory providing computing cycles and large amoun...
[[abstract]]The paper describes a parallel file object environment to support distributed array stor...
Parallel systems leverage parallel file systems to efficiently perform I/O to shared files. These pa...
Languages such as High Performance Fortran implement parallel algorithms by distributing large data ...
[[abstract]]This paper presents a parallel file object environment to support distributed array stor...
This thesis presents a generalized framework for the mapping and remapping of large regularly-gridd...
We present algorithms for the transportation of data in parallel and distributed systems that would ...
Datasets in large scale scientific data management, are often modeled as k-dimensional arrays. Eleme...
In many existing and planned parallel machines, memory cannot be considered as a single homogeneous ...
This paper addresses the problem of providing a parallel virtual memory system with an efficient swa...
The optimal mapping of tasks of a parallel program onto nodes of a parallel computing system has a r...
Parallel input/output in high performance computing is a field of increasing importance. In particul...
In this paper we present a method to obtain a set of candidate distributions for a program fragment....
Massively Parallel Processor systems provide the required computational power to solve most large sc...
We consider distribution at compile time of the array data in a distributed-memory implementation of...
Parallel architectures with physically distributed memory providing computing cycles and large amoun...
[[abstract]]The paper describes a parallel file object environment to support distributed array stor...
Parallel systems leverage parallel file systems to efficiently perform I/O to shared files. These pa...
Languages such as High Performance Fortran implement parallel algorithms by distributing large data ...
[[abstract]]This paper presents a parallel file object environment to support distributed array stor...
This thesis presents a generalized framework for the mapping and remapping of large regularly-gridd...
We present algorithms for the transportation of data in parallel and distributed systems that would ...
Datasets in large scale scientific data management, are often modeled as k-dimensional arrays. Eleme...
In many existing and planned parallel machines, memory cannot be considered as a single homogeneous ...
This paper addresses the problem of providing a parallel virtual memory system with an efficient swa...
The optimal mapping of tasks of a parallel program onto nodes of a parallel computing system has a r...
Parallel input/output in high performance computing is a field of increasing importance. In particul...
In this paper we present a method to obtain a set of candidate distributions for a program fragment....
Massively Parallel Processor systems provide the required computational power to solve most large sc...
We consider distribution at compile time of the array data in a distributed-memory implementation of...
Parallel architectures with physically distributed memory providing computing cycles and large amoun...
[[abstract]]The paper describes a parallel file object environment to support distributed array stor...