This paper gives an overview of the implementation of NESL, a portable nested data-parallel language. This language and its implementation are the first to fully support nested data structures as well as nested data-parallel function calls. These features allow the concise description of parallel algorithms on irregular data structures, such as sparse matrices and graphs. In addition, they maintain the advantages of data-parallel languages: a simple programming model and portability. The current NESL implementation is based on an intermediate language called VCODE and a library of vector routines called CVL. It runs on the Connection Machines CM-2 and CM-5, the Cray C90, and serial workstations. We compare initial benchmark results of NESL ...
The success of parallel architectures has been limited by the lack of high-level parallel programmin...
Nested data-parallelism (NDP) is a declarative style for program-ming irregular parallel application...
This paper describes two portable packages for general-purpose sparse matrix computations: SPARSKIT...
This paper gives an overview of the implementation of Nesl, a portable nested data-parallel language...
This report describes Nesl, a strongly-typed, applicative, data-parallel language. Nesl is intended ...
Graphics processing units (GPUs) provide both memory bandwidth and arithmetic performance far greate...
This report introduces VCODE, an intermediate language for data-parallel computations. VCODE is desi...
. The Numerical Algorithms Group Ltd is currently participating in the European HPCN Fourth Framewor...
Data parallelislm is one of the more successful efforts to introduce explicit parallelism to high le...
Sparse matrices are first class objects in many VHLLs (very high level languages) used for scientifi...
The purpose of the Adl project is to demonstrate the efficient implementation of data parallel funct...
Sparse matrix formats encode very large numerical matrices with relatively few nonzeros. They are ty...
This paper describes the integration of nested data parallelism into imperative languages using the ...
Contemporary parallel microprocessors exploit Chip Multiprocessing along with Single Instruction, Mu...
This paper proposes a new approach to improve data-parallel languages in the context of sparse and i...
The success of parallel architectures has been limited by the lack of high-level parallel programmin...
Nested data-parallelism (NDP) is a declarative style for program-ming irregular parallel application...
This paper describes two portable packages for general-purpose sparse matrix computations: SPARSKIT...
This paper gives an overview of the implementation of Nesl, a portable nested data-parallel language...
This report describes Nesl, a strongly-typed, applicative, data-parallel language. Nesl is intended ...
Graphics processing units (GPUs) provide both memory bandwidth and arithmetic performance far greate...
This report introduces VCODE, an intermediate language for data-parallel computations. VCODE is desi...
. The Numerical Algorithms Group Ltd is currently participating in the European HPCN Fourth Framewor...
Data parallelislm is one of the more successful efforts to introduce explicit parallelism to high le...
Sparse matrices are first class objects in many VHLLs (very high level languages) used for scientifi...
The purpose of the Adl project is to demonstrate the efficient implementation of data parallel funct...
Sparse matrix formats encode very large numerical matrices with relatively few nonzeros. They are ty...
This paper describes the integration of nested data parallelism into imperative languages using the ...
Contemporary parallel microprocessors exploit Chip Multiprocessing along with Single Instruction, Mu...
This paper proposes a new approach to improve data-parallel languages in the context of sparse and i...
The success of parallel architectures has been limited by the lack of high-level parallel programmin...
Nested data-parallelism (NDP) is a declarative style for program-ming irregular parallel application...
This paper describes two portable packages for general-purpose sparse matrix computations: SPARSKIT...