Many-body computing on Field Programmable Gate Arrays

A new implementation of many-body calculations is of paramount importance in the field of computational physics. In this study, we leverage the capabilities of Field Programmable Gate Arrays (FPGAs) for conducting quantum many-body calculations. Through the design of appropriate schemes for Monte Carlo and tensor network methods, we effectively utilize the parallel processing capabilities provided by FPGAs. This has resulted in a tenfold speedup compared to CPU-based computation for a Monte Carlo algorithm. By using a supercell structure and simulating the FPGA architecture on a CPU with High-Level Synthesis, we achieve $O(1)$ scaling for the time of one sweep, regardless of the overall system size. We also demonstrate, for the first time, the utilization of FPGA to accelerate a typical tensor network algorithm for many-body ground state calculations. Additionally, we show that the current FPGA computing acceleration is on par with that of multi-threaded GPU parallel processing. Our findings unambiguously highlight the significant advantages of hardware implementation and pave the way for novel approaches to many-body calculations.