Maximizing the productivity of modern multicore and manycore chips requires optimizing parallelism at the compute node level. This is, however, a complex multi-step process. It is an iterative method requiring determining optimal degrees of parallel scalability and optimizing memory access behavior. Further, there are multiple cases to be considered, programs which use only MPI or OpenMP and hybrid (MPI +OpenMP) programs. This paper presents a set of three coordinated workflows for determining the optimal parallelism at the program level for MPI programs and at the loop level for hybrid (MPI+OpenMP) cases. The paper also details mostly automated implementations of these workflows using the PerfExpert infrastructure. Finally the paper presents...
Many/multi-core supercomputers provide a natural programming paradigm for hybrid MPI/OpenMP scientif...
Significantly increasing intra-node parallelism is widely recognised as being a key prerequisite for...
With the introduction of more powerful and massively parallel embedded processors, embedded systems ...
Maximizing the productivity of modern multicore and manycore chips requires optimizing parallelism a...
MPI is the predominant model for parallel programming in technical high performance computing. With ...
Abstract. The Hybrid method of parallelization (using MPI for inter-node communication and OpenMP fo...
After a brief introduction on Cross Motif Search and its OpenMP and Hybrid OpenMP-MPI implementatio...
Overview Most HPC systems are clusters of shared memory nodes. To use such systems efficiently both...
The mixing of shared memory and message passing programming models within a single application has o...
Most HPC systems are clusters of shared memory nodes. To use such systems efficiently both memory co...
This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Compute...
The most widely used node type in high-performance computing nowadays is a 2-socket server node. The...
Most HPC systems are clusters of shared memory nodes. Parallel programming must combine the distribu...
Holistic tuning and optimization of hybrid MPI and OpenMP applications is becoming focus for paralle...
Most HPC systems are clusters of shared memory nodes. Parallel programming must combine the distribu...
Many/multi-core supercomputers provide a natural programming paradigm for hybrid MPI/OpenMP scientif...
Significantly increasing intra-node parallelism is widely recognised as being a key prerequisite for...
With the introduction of more powerful and massively parallel embedded processors, embedded systems ...
Maximizing the productivity of modern multicore and manycore chips requires optimizing parallelism a...
MPI is the predominant model for parallel programming in technical high performance computing. With ...
Abstract. The Hybrid method of parallelization (using MPI for inter-node communication and OpenMP fo...
After a brief introduction on Cross Motif Search and its OpenMP and Hybrid OpenMP-MPI implementatio...
Overview Most HPC systems are clusters of shared memory nodes. To use such systems efficiently both...
The mixing of shared memory and message passing programming models within a single application has o...
Most HPC systems are clusters of shared memory nodes. To use such systems efficiently both memory co...
This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Compute...
The most widely used node type in high-performance computing nowadays is a 2-socket server node. The...
Most HPC systems are clusters of shared memory nodes. Parallel programming must combine the distribu...
Holistic tuning and optimization of hybrid MPI and OpenMP applications is becoming focus for paralle...
Most HPC systems are clusters of shared memory nodes. Parallel programming must combine the distribu...
Many/multi-core supercomputers provide a natural programming paradigm for hybrid MPI/OpenMP scientif...
Significantly increasing intra-node parallelism is widely recognised as being a key prerequisite for...
With the introduction of more powerful and massively parallel embedded processors, embedded systems ...