Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Take a multicore Digital Signal Processor (DSP) chip designed for cellular base stations and radio network controllers, add floating-point capabilities to support 4G networks, and out of thin air a HPC engine is born. The potential for HPC is clear: It promises 128 GFLOPS (single precision) for 10 Watts; It is used in millions of network related devices and hence benefits from economies of scale; It should be simpler to program than a GPU. Simply put, it is fast, green, and cheap. But is it easy to use? ,  show how this potential can be applied to general-purpose high performance computing, more specifically to dense matrix computations, without major changes in existing codes and methodologies, and with excellent performance and por consumption numbers.
['Francisco D. Igual', 'Murtaza Ali', 'Arnon Friedmann', 'Eric J. Stotzer', 'Timothy Wentz', 'Robert A. van de Geijn']
I am writing a research paper on a idea Unleashing the high-performance and low-power of multi-core DSPs for general-purpose HPC
[{"from": "human", "value": "I am writing a research paper on a idea Unleashing the high-performance and low-power of multi-core DSPs for general-purpose HPC"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Take a multicore Digital Signal Processor (DSP) chip designed for cellular base stations and radio network controllers, add floating-point capabilities to support 4G networks, and out of thin air a HPC engine is born. The potential for HPC is clear: It promises 128 GFLOPS (single precision) for 10 Watts; It is used in millions of network related devices and hence benefits from economies of scale; It should be simpler to program than a GPU. Simply put, it is fast, green, and cheap. But is it easy to use? ,  show how this potential can be applied to general-purpose high performance computing, more specifically to dense matrix computations, without major changes in existing codes and methodologies, and with excellent performance and por consumption numbers."}]