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Heliostat: Harnessing Ray Tracing Accelerators for Page Table Walks – ISCA 2025 [video]

Posted by matt_d |4 hours ago |1 comments

matt_d 4 hours ago

Paper: https://doi.org/10.1145/3695053.3731011

PDF: https://dl.acm.org/doi/pdf/10.1145/3695053.3731011

Abstract: This paper introduces Heliostat, which enhances page translation bandwidth on GPUs by harnessing underutilized ray tracing accelerators (RTAs). While most existing studies focused on better utilizing the provided translation bandwidth, this paper introduces a new opportunity to fundamentally increase the translation bandwidth. Instead of overprovisioning the GPU memory management unit (GMMU), Heliostat repurposes the existing RTAs by leveraging the operational similarities between ray tracing and page table walks. Unlike earlier studies that utilized RTAs for certain workloads, Heliostat democratizes RTA for supporting any workloads by improving virtual memory performance. Heliostat+ optimizes Heliostat by handling predicted future address translations proactively. Heliostat outperforms baseline and two state-of-the-arts by 1.93 ×, 1.92 ×, and 1.66 ×. Heliostat+ further speeds up Heliostat by 1.23 ×. Compared to an overprovisioned comparable solution, Heliostat occupies only 1.53% of the area and consumes 5.8% of the power.