Tyche: A Compact and Configurable Accelerator for Scalable Probabilistic Computing on FPGA

Yashash Jain,Utsav Banerjee

2023 IEEE HIGH PERFORMANCE EXTREME COMPUTING CONFERENCE, HPEC(2023)

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摘要
Probabilistic computing is an emerging computing paradigm which involves the systematic control and manipulation of unstable stochastic units called p-bits. Multiple p-bits are connected together to implement p-circuits which have been shown to be capable of solving interesting computationally hard problems. In this work, we present Tyche, a compact and configurable hardware accelerator for scalable probabilistic computing on FPGA. Our architecture allows p-circuits requiring different number of p-bits to be implemented using the same hardware. The use of a single p-bit computing core instead of an array of processing elements provides significant logic resource savings. A logarithmic adder tree is used for single-cycle weight logic computation while ensuring reasonable performance even for large number of p-bits. Various application-specific p-circuits are experimentally demonstrated using our proposed hardware accelerator implemented on Xilinx UltraScale+ FPGA, thus emphasizing the viability of practical scalable probabilistic computing on modern FPGAs.
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关键词
FPGA,probabilistic computing,configurable accelerator,binary stochastic neuron,p-bit,p-circuit,invertible logic,Boltzmann machine,Ising machine,integer factorization
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