S. Moore, P. Fox, Steven Jt, Marsh, A. T. Markettos, A. Mujumdar
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引用次数: 102
Abstract
Bluehive is a custom 64-FPGA machine targeted at scientific simulations with demanding communication requirements. Bluehive is designed to be extensible with a reconfigurable communication topology suited to algorithms with demanding high-bandwidth and low-latency communication, something which is unattainable with commodity GPGPUs and CPUs. We demonstrate that a spiking neuron algorithm can be efficiently mapped to Bluehive using Bluespec System Verilog by taking a communication-centric approach. This contrasts with many FPGA-based neural systems which are very focused on parallel computation, resulting in inefficient use of FPGA resources. Our design allows 64k neurons with 64M synapses per FPGA and is scalable to a large number of FPGAs.
Bluehive是一款定制的64-FPGA机器,针对具有苛刻通信要求的科学模拟。Bluehive被设计为可扩展的可重构通信拓扑,适合要求高带宽和低延迟通信的算法,这是商品gpgpu和cpu无法实现的。我们证明了通过采用以通信为中心的方法,使用Bluespec System Verilog可以有效地将峰值神经元算法映射到Bluehive。这与许多基于FPGA的神经系统形成鲜明对比,这些系统非常注重并行计算,导致FPGA资源的低效使用。我们的设计允许每个FPGA有64k个神经元和64M个突触,并且可以扩展到大量FPGA。