Toki is the first hardware-software framework that enables profiling the performance of HBM on FPGA accelerator cards by jointly considering the execution of workloads on RISC-V soft cores instantiated on the FPGA and the injection of memory traffic from the host system via DMA over PCIe, providing insights that cannot be obtained with synthetic traffic generators alone.
Abstract
Programmable RISC-V soft cores are becoming more widespread in data-center scenarios, making it crucial to design efficient systems that deploy them on FPGA chips with HBM memory. Toki, released as open source, is the first hardware-software framework that enables profiling the performance of HBM on FPGA accelerator cards by jointly considering (i) the execution of workloads on RISC-V soft cores instantiated on the FPGA and (ii) the injection of memory traffic from the host system via DMA over PCIe, providing insights that cannot be obtained with synthetic traffic generators alone. Extensive experiments target an AMD Alveo U55C card, deploying up to 60 RISC-V compute cores and stressing its HBM2 memory through real-world applications and microbenchmarks with user-defined access patterns. Results showcase how Toki can effectively profile the impact on HBM performance of the compute cores'organization, the workload's memory access patterns, data locality, contention over the memory controllers, and host traffic.
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