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This article presents a 32-bit floating-point (FP32) programmable accelerator for solving a wide range of partial differential equations (PDEs) based on numerical integration methods. Compared to prior works that have fixed-point systems and are only applicable to specific types of PDEs, our proposed, integration accelerator for PDEs, named INTIACC, accelerator consists of 16 locally interconnected processing elements (PEs) where each PE is a fully programmable reduced instruction set computer (RISC) processor with an FP32 arithmetic logic unit (FP32 ALU) and a custom-designed instruction set architecture (ISA). These features enable INTIACC to generate solutions with high precision and a wide dynamic range and also allow users to implement different numerical algorithms to perform high-order integration methods and to evaluate nonlinear functions. In addition, we create a novel slow-global-fast-local clocking scheme in which PEs operate asynchronously with each other most of the time. We prototype the INTIACC test chip in 65 nm, with a core area of 0.975 mm2. Running at an average local clock frequency of 570 MHz at 1 V, it offers a single-precision computation throughput of 9.12 GFLOPS. Testing results show that with a similar energy-delay product, INTIACC is up to 40× faster than the prior state-of-the-art PDE solver. 

We propose a numerical integration accelerator (INTIACC) that speeds up the solution of partial differential equations (PDEs) for scientific computing. In contrast to recent works, INTIACC applies to a variety of PDEs and boundary conditions, has enhanced nonlinear function capability, supports high-order integration algorithms, and uses floating-point arithmetic for orders of magnitude smaller solution error. With all the benefits, our test chip still achieves 40X speed-up over prior accelerators and orders of magnitudes over CPU and GPU based systems.