Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Heterogeneous architectures with single-ISA asymmetric cores have the potential to improve both the performance and energy efficiency of software execution by dynamically selecting the most appropriate core type to run each execution thread. ,  propose a trace-based methodology to explore por and performance benefits of single-ISA heterogeneous core architectures. The basic idea is to collect multiple traces by running a workload on different homogeneous platforms, and to align these traces for offline analysis. For this,  propose a wavelet-based similarity metric, which captures both fine-grain and coarse-grain software phases across different traces. Then,  propose a scalable dynamic programming algorithm to optimize this metric to align the traces. Our experiments show that the runtime and energy values predicted by our offline methodology have good accuracy with respect to the real measurements from a prototype heterogeneous system. The proposed methodology can enable design space exploration of single-ISA heterogeneous multi-core systems using traces from off-the-shelf homogeneous systems.
['Muhammet Mustafa Ozdal', 'Aamer Jaleel', 'Paolo Narvaez', 'Steven M. Burns', 'Ganapati Srinivasa']
I am writing a research paper on a idea Trace alignment algorithms for offline workload analysis of heterogeneous architectures
[{"from": "human", "value": "I am writing a research paper on a idea Trace alignment algorithms for offline workload analysis of heterogeneous architectures"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Heterogeneous architectures with single-ISA asymmetric cores have the potential to improve both the performance and energy efficiency of software execution by dynamically selecting the most appropriate core type to run each execution thread. ,  propose a trace-based methodology to explore por and performance benefits of single-ISA heterogeneous core architectures. The basic idea is to collect multiple traces by running a workload on different homogeneous platforms, and to align these traces for offline analysis. For this,  propose a wavelet-based similarity metric, which captures both fine-grain and coarse-grain software phases across different traces. Then,  propose a scalable dynamic programming algorithm to optimize this metric to align the traces. Our experiments show that the runtime and energy values predicted by our offline methodology have good accuracy with respect to the real measurements from a prototype heterogeneous system. The proposed methodology can enable design space exploration of single-ISA heterogeneous multi-core systems using traces from off-the-shelf homogeneous systems."}]