Parallelization of sequential application programs for distributed memory machines generally involves non-local modifications to the program code. Thus, for large applications, it may be very time-consuming even to experiment with different parallelization strategies for only relatively small computational kernels. TOP2 is an interactive programming environment developed at KFA/ZAM supporting partial parallelization of large applications for distributed memory multiprocessors, especially Intel iPSC/860 and Intel Paragon. It allows the user to experiment with different parallelization strategies on the basis of individual subroutines
Distributed Memory Multicomputers (DMMs) such as the IBM SP-2, the Intel Paragon and the Thinking Ma...
Programming distributed memory systems forces the user to handle the problem of data locality. With ...
It has become common knowledge that parallel programming is needed for scientific applications, part...
Parallelization of sequential programs for distributed memory machines generally involves non-local ...
Parallelization of sequential programs for distributed memory machines generally involves non-local ...
TOP2 is a tool suite that aids users of parallel systems with distributed memory in porting existing...
TOP2 is a tool suite that aids users of parallel systems with distributed memory in porting existing...
The parallelization of real-world compute intensive Fortran application codes is generally not a tri...
The end of Dennard scaling also brought an end to frequency scaling as a means to improve performanc...
This chapter discusses the code parallelization environment, where a number of tools that address th...
An extensible machine architecture is devised to efficiently support a parallel reduction model of c...
International audienceIn this paper, we focus on a distributed and parallel programming paradigm for...
Distributed-memory multiprocessing systems (DMS), such as Intel’s hypercubes, the Paragon, Thinking ...
In machines like the Intel iPSC/2 and the BBN Butterfly, local memory operations are much faster tha...
A faire apr`es Keywords: Parallel environment, Distributed-memory machines, Load-balancing, Mapping...
Distributed Memory Multicomputers (DMMs) such as the IBM SP-2, the Intel Paragon and the Thinking Ma...
Programming distributed memory systems forces the user to handle the problem of data locality. With ...
It has become common knowledge that parallel programming is needed for scientific applications, part...
Parallelization of sequential programs for distributed memory machines generally involves non-local ...
Parallelization of sequential programs for distributed memory machines generally involves non-local ...
TOP2 is a tool suite that aids users of parallel systems with distributed memory in porting existing...
TOP2 is a tool suite that aids users of parallel systems with distributed memory in porting existing...
The parallelization of real-world compute intensive Fortran application codes is generally not a tri...
The end of Dennard scaling also brought an end to frequency scaling as a means to improve performanc...
This chapter discusses the code parallelization environment, where a number of tools that address th...
An extensible machine architecture is devised to efficiently support a parallel reduction model of c...
International audienceIn this paper, we focus on a distributed and parallel programming paradigm for...
Distributed-memory multiprocessing systems (DMS), such as Intel’s hypercubes, the Paragon, Thinking ...
In machines like the Intel iPSC/2 and the BBN Butterfly, local memory operations are much faster tha...
A faire apr`es Keywords: Parallel environment, Distributed-memory machines, Load-balancing, Mapping...
Distributed Memory Multicomputers (DMMs) such as the IBM SP-2, the Intel Paragon and the Thinking Ma...
Programming distributed memory systems forces the user to handle the problem of data locality. With ...
It has become common knowledge that parallel programming is needed for scientific applications, part...