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ASPLOS2023顶会

Skybox: Open-Source Graphic Rendering on Programmable RISC-V GPUs

Blaise Tine, Varun Saxena, Santosh Srivatsan, Joshua R. Simpson, Fadi Alzammar, Liam Cooper, Hyesoon Kim

2023年份
17被引次数
4顶会引用

摘要

Graphics rendering remains one of the most compute intensive and memory bound applications of GPUs and has been driving their push for performance and energy efficiency since its inception. Early GPU architectures focused only on accelerating graphics rendering and implemented dedicated fixed- function rasterizer hardware to speed-up their rendering pipeline. As GPUs have become more programmable and ubiquitous in other application domains such as scientific computing, machine learning, graph analytics, and crypto-currency, generalizing GPU microarchitectures for area and power efficiency becomes necessary, especially for mobile and IoT devices. In this work, we present Skybox, a full-stack open-source GPU architecture with integrated software, compiler, hardware, and simulation environment, that enables end-to-end GPU research. Using Skybox, we explore the design space of software versus hardware graphics rendering and propose and hybrid micro-architecture that accelerates the state-of-the art Vulkan graphics API. Skybox also introduces novel compiler and system optimizations to support its unique RISC-V ISA baseline. We evaluated Skybox on high- end Altera and also Xilinx FPGAs. We were able to generate and execute a 32 cores (512 threads) Skybox graphics processor on Altera Stratix 10 FPGA, delivering a peak fill rate of 3.7 GPixels at 230 MHz. Skybox is the first open-source full-stack GPU software and hardware implementation that supports the Vulkan API

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