Employing FPGAs for computing purposes requires a mapping process. Although this procedure saves sub-stantial development time compared to the physical de-sign of an ASIC, several mappings are almost always needed until the constraints can be met. The Perfor-mance Prediction Model (PPM) is a means to help re-ducing the development time while providing an esti-mation of the performance to be achieved. The estima-tion is based on a preliminary implementation1 only and separates different influences, which improves its portability. The PPM yields an accuracy of about 10% in average and is thus suitable for finding a good im-plementation for starting the actual mapping process.
High-performance computing is essential for solving large problems and for reducing the time to solu...
this paper are generated by an execution-driven performance simulator [2]. The simulator uses a cycl...
ii The current trend in High-Performance Computing (HPC) is to extract concurrency from clusters tha...
During the design of complex systems, designers need to know how their algorithm or hardware is goi...
Advances in digital computers have been spectacular but increasingly complex to model. Even the cycl...
International audienceApplication mapping in multicore embedded systems plays a central role in thei...
CPUs and dedicated accelerators (namely GPUs and FPGAs) continue to grow increasingly large and comp...
A common approach to studying future computer systems is to build simulators that accurately model t...
A method is presented for modeling application performance on parallel computers in terms of the per...
In this paper, we discuss different approaches to performance prediction of embedded systems. We dis...
Model-based performance prediction is a well-known concept to ensure the quality of software.Current...
We concern ourselves in this paper with one important application of predictive performance modeling...
The significant growth in computational power of mod-ern Graphics Processing Units(GPUs) coupled wit...
Traditional means of gathering performance data are trac-ing, which is limited by the available stor...
Performance is one of the key features of parallel and distributed computing systems. Therefore, in ...
High-performance computing is essential for solving large problems and for reducing the time to solu...
this paper are generated by an execution-driven performance simulator [2]. The simulator uses a cycl...
ii The current trend in High-Performance Computing (HPC) is to extract concurrency from clusters tha...
During the design of complex systems, designers need to know how their algorithm or hardware is goi...
Advances in digital computers have been spectacular but increasingly complex to model. Even the cycl...
International audienceApplication mapping in multicore embedded systems plays a central role in thei...
CPUs and dedicated accelerators (namely GPUs and FPGAs) continue to grow increasingly large and comp...
A common approach to studying future computer systems is to build simulators that accurately model t...
A method is presented for modeling application performance on parallel computers in terms of the per...
In this paper, we discuss different approaches to performance prediction of embedded systems. We dis...
Model-based performance prediction is a well-known concept to ensure the quality of software.Current...
We concern ourselves in this paper with one important application of predictive performance modeling...
The significant growth in computational power of mod-ern Graphics Processing Units(GPUs) coupled wit...
Traditional means of gathering performance data are trac-ing, which is limited by the available stor...
Performance is one of the key features of parallel and distributed computing systems. Therefore, in ...
High-performance computing is essential for solving large problems and for reducing the time to solu...
this paper are generated by an execution-driven performance simulator [2]. The simulator uses a cycl...
ii The current trend in High-Performance Computing (HPC) is to extract concurrency from clusters tha...