Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The Inferior-Olivary nucleus ION is a ll-charted brain region, heavily associated with the sensorimotor control of the body. It comprises neural cells with unique properties which facilitate sensory processing and motor-learning skills. Simulations of such neurons become rapidly intractable when biophysically plausible models and meaningful network sizes at least in the order of some hundreds of cells are modeled. To overcome this problem,  accelerate a highly detailed ION network model using a Maxeler Dataflow Computing Machine. The design simulates a 330-cell network at real-time speed and achieves maximum throughputs of 24.7 GFLOPS. The Maxeler machine, integrating a Virtex-6 FPGA, yields speedups of ×92-102, and ×2-8 compared to a reference-C implementation, running on a Intel Xeon 2.66GHz, and a pure Virtex-7 FPGA implementation, respectively.
['Georgios Smaragdos', 'Craig Davies', 'Christos Strydis', 'Ioannis Sourdis', 'Catalin Bogdan Ciobanu', 'Oskar Mencer', 'Chris I. De Zeeuw']
I am writing a research paper on a idea Real-Time Olivary Neuron Simulations on Dataflow Computing Machines
[{"from": "human", "value": "I am writing a research paper on a idea Real-Time Olivary Neuron Simulations on Dataflow Computing Machines"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The Inferior-Olivary nucleus ION is a ll-charted brain region, heavily associated with the sensorimotor control of the body. It comprises neural cells with unique properties which facilitate sensory processing and motor-learning skills. Simulations of such neurons become rapidly intractable when biophysically plausible models and meaningful network sizes at least in the order of some hundreds of cells are modeled. To overcome this problem,  accelerate a highly detailed ION network model using a Maxeler Dataflow Computing Machine. The design simulates a 330-cell network at real-time speed and achieves maximum throughputs of 24.7 GFLOPS. The Maxeler machine, integrating a Virtex-6 FPGA, yields speedups of \u00d792-102, and \u00d72-8 compared to a reference-C implementation, running on a Intel Xeon 2.66GHz, and a pure Virtex-7 FPGA implementation, respectively."}]