Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Stringent performance targets and por constraints push designers towards building specialized workload-optimized systems across a broad spectrum of the computing arena, including supercomputing applications as exemplified by the IBM BlueGene and Intel MIC architectures. ,  make the case for hardware/software co-design during early design stages of processors for scientific computing applications. Considering an important scientific kernel, namely stencil computation,  demonstrate that performance and energy-efficiency can be improved by a factor of 1.66× and 1.25×, respectively, by co-optimizing hardware and software. To enable hardware/software co-design in early stages of the design cycle,  propose a novel simulation infrastructure by combining high-abstraction performance simulation using Sniper with por modeling using McPAT and custom DRAM por models. Sniper/McPAT is fast — simulation speed is around 2 MIPS on an 8-core host machine — because it uses analytical modeling to abstract away core performance during multi-core simulation.  demonstrate Sniper/McPAT's accuracy through validation against real hardware;  report average performance and por prediction errors of 22.1% and 8.3%, respectively, for a set of SPEComp benchmarks.
['Wim Heirman', 'Souradip Sarkar', 'Trevor E. Carlson', 'Ibrahim Hur', 'Lieven Eeckhout']
I am writing a research paper on a idea Power-aware multi-core simulation for early design stage hardware/software co-optimization
[{"from": "human", "value": "I am writing a research paper on a idea Power-aware multi-core simulation for early design stage hardware/software co-optimization"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Stringent performance targets and por constraints push designers towards building specialized workload-optimized systems across a broad spectrum of the computing arena, including supercomputing applications as exemplified by the IBM BlueGene and Intel MIC architectures. ,  make the case for hardware/software co-design during early design stages of processors for scientific computing applications. Considering an important scientific kernel, namely stencil computation,  demonstrate that performance and energy-efficiency can be improved by a factor of 1.66\u00d7 and 1.25\u00d7, respectively, by co-optimizing hardware and software. To enable hardware/software co-design in early stages of the design cycle,  propose a novel simulation infrastructure by combining high-abstraction performance simulation using Sniper with por modeling using McPAT and custom DRAM por models. Sniper/McPAT is fast \u2014 simulation speed is around 2 MIPS on an 8-core host machine \u2014 because it uses analytical modeling to abstract away core performance during multi-core simulation.  demonstrate Sniper/McPAT's accuracy through validation against real hardware;  report average performance and por prediction errors of 22.1% and 8.3%, respectively, for a set of SPEComp benchmarks."}]