PiMulator: a Fast and Flexible Processing-in-Memory Emulation Platform

PROCEEDINGS OF THE 2022 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE 2022)(2022)

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摘要
Motivated by the memory wall problem, researchers propose many new Processing-in-Memory (PiM) architectures to bring computation closer to data. However, evaluating the performance of these emerging architectures involves using a myriad of tools, including circuit simulators, behavioral RTL or software simulation models, hardware approximations, etc. It is challenging to mimic both software and hardware aspects of a PiM architecture using the currently available tools with high performance and fidelity. Until and unless actual products that include PiM become available, the next best thing is to emulate various hardware PiM solutions on FPGA fabric and boards. This paper presents a modular, parameterizable, FPGA synthesizable soft PiM model suitable for prototyping and rapid evaluation of Processing-in-Memory architectures. The PiM model is implemented in System Verilog and allows users to generate any desired memory configuration on the FPGA fabric with complete control over the structure and distribution of the PiM logic units. Moreover, the model is compatible with the LiteX framework, which provides a high degree of usability and compatibility with the FPGA and RISC-V ecosystem. Thus, the framework enables architects to easily prototype, emulate and evaluate a wide range of emerging PiM architectures and designs. We demonstrate strategies to model several pioneering bitwisePiM architectures and provide detailed benchmark performance results that demonstrate the platform's ability to facilitate design space exploration. We observe an emulation vs. simulation weighted-average speedup of 28x when running a memory benchmark workload. The model can utilize 100% BRAM and only 1% FF and LUT of an Alveo U280 FPGA board. The project is entirely open-source.
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关键词
FPGA Emulation, Fidelity, Simulation Wall, Processing-in-Memory (PiM), High-Bandwidth Memory (HBM)
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