Power efficiency became an important factor in High Performance Computing (HPC). FPGA-based dataflow machines are the best candidates for power efficient computing, because of the maximized memory bandwidth utilization, and user-defined optimal caching. However, input data streams are required with optimized data locality. This paper focuses on the possibilities of novel mesh partitioning techniques, which provide partitions with better data locality
In many-task computing (MTC), applications such as scientific workflows or parameter sweeps communic...
In many-task computing (MTC), applications such as scientific workflows or parameter sweeps communic...
This paper describes a technique for improving the data ref-erence locality of parallel programs usi...
Abstract—Heterogeneous computing using FPGA accelerators is a promising approach to boost the perfor...
The cost of data movement has always been an important concern in high performance computing (HPC) s...
Many real-life applications of processor-arrays suffer from memory bandwidth limitations. In many ca...
As we observe diminishing returns for multi-core CPUs, especially when considering power budgets, FP...
The massive parallelism provided by general-purpose GPUs (GPGPUs) possessing numerous compute thread...
Reconfigurable computing systems show great promise for accelerating streaming HPC applications beca...
Unstructured-mesh based numerical algorithms such as finite volume and finite element algorithms for...
Abstract—Modern computing platforms are increasingly com-plex, with multiple cores, shared caches, a...
Big data has revolutionized science and technology leading to the transformation of our societies. H...
Abstract—Common practice for large FPGA design projects is to divide sub-projects into separate synt...
Applications that operate on meshes are very popular in High Performance Computing (HPC) environment...
The dataflow supercomputer outperforms the conventional multi-core supercomputers based on CPU/ GPUs...
In many-task computing (MTC), applications such as scientific workflows or parameter sweeps communic...
In many-task computing (MTC), applications such as scientific workflows or parameter sweeps communic...
This paper describes a technique for improving the data ref-erence locality of parallel programs usi...
Abstract—Heterogeneous computing using FPGA accelerators is a promising approach to boost the perfor...
The cost of data movement has always been an important concern in high performance computing (HPC) s...
Many real-life applications of processor-arrays suffer from memory bandwidth limitations. In many ca...
As we observe diminishing returns for multi-core CPUs, especially when considering power budgets, FP...
The massive parallelism provided by general-purpose GPUs (GPGPUs) possessing numerous compute thread...
Reconfigurable computing systems show great promise for accelerating streaming HPC applications beca...
Unstructured-mesh based numerical algorithms such as finite volume and finite element algorithms for...
Abstract—Modern computing platforms are increasingly com-plex, with multiple cores, shared caches, a...
Big data has revolutionized science and technology leading to the transformation of our societies. H...
Abstract—Common practice for large FPGA design projects is to divide sub-projects into separate synt...
Applications that operate on meshes are very popular in High Performance Computing (HPC) environment...
The dataflow supercomputer outperforms the conventional multi-core supercomputers based on CPU/ GPUs...
In many-task computing (MTC), applications such as scientific workflows or parameter sweeps communic...
In many-task computing (MTC), applications such as scientific workflows or parameter sweeps communic...
This paper describes a technique for improving the data ref-erence locality of parallel programs usi...