Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Several techniques have been proposed to enhance the energy-efficiency of ASIPs (Application-Specific Instruction set Processors). While those techniques can reduce the energy consumption with a minimal change in the instruction set (IS), they fail to exploit the opportunity of designing the entire IS from the energy-efficiency perspective. ,  present an energy-efficient IS synthesis technique that can comprehensively reduce the energy-delay product (EDP) of ASIPs through optimal instruction encoding, considering both the instruction bitwidth and the dynamic instruction count. Experimental results with a typical embedded RISC processor show that our technique can generate application-specific IS's that are up to 40% more energy-efficient over the native IS for several application benchmarks.
['Jongeun Lee', 'Kiyoung Choi', 'Nikil Dutt']
I am writing a research paper on a idea Energy-efficient instruction set synthesis for application-specific processors
[{"from": "human", "value": "I am writing a research paper on a idea Energy-efficient instruction set synthesis for application-specific processors"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Several techniques have been proposed to enhance the energy-efficiency of ASIPs (Application-Specific Instruction set Processors). While those techniques can reduce the energy consumption with a minimal change in the instruction set (IS), they fail to exploit the opportunity of designing the entire IS from the energy-efficiency perspective. ,  present an energy-efficient IS synthesis technique that can comprehensively reduce the energy-delay product (EDP) of ASIPs through optimal instruction encoding, considering both the instruction bitwidth and the dynamic instruction count. Experimental results with a typical embedded RISC processor show that our technique can generate application-specific IS's that are up to 40% more energy-efficient over the native IS for several application benchmarks."}]