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OOPSLA2021顶会

Specifying and testing GPU workgroup progress models

Tyler Sorensen, Lucas F. Salvador, Harmit Raval, Hugues Evrard, John Wickerson, Margaret Martonosi, Alastair F. Donaldson

2021年份
11被引次数
6顶会引用

摘要

As GPU availability has increased and programming support has matured, a wider variety of applications are being ported to these platforms. Many parallel applications contain fine-grained synchronization idioms; as such, their correct execution depends on a degree of relative forward progress between threads (or thread groups). Unfortunately, many GPU programming specifications (e.g. Vulkan and Metal) say almost nothing about relative forward progress guarantees between workgroups. Although prior work has proposed a spectrum of plausible progress models for GPUs, cross-vendor specifications have yet to commit to any model.

This work is a collection of tools and experimental data to aid specification designers when considering forward progress guarantees in programming frameworks. As a foundation, we formalize a small parallel programming language that captures the essence of fine-grained synchronization. We then provide a means of formally specifying a progress model, and develop a termination oracle that decides whether a given program is guaranteed to eventually terminate with respect to a given progress model. Next, we formalize a set of constraints that describe concurrent programs that require forward progress to terminate. This allows us to synthesize a large set of 483 progress litmus tests. Combined with the termination oracle, we can determine the expected status of each litmus test -i.e. whether it is guaranteed to eventually terminate -under various progress models. We present a large experimental campaign running the litmus tests across 8 GPUs from 5 different vendors. Our results highlight that GPUs have significantly different termination behaviors under our test suite. Most notably, we find that Apple and ARM GPUs do not support the linear occupancy-bound model, an intuitive progress model defined by prior work that has been hypothesized to describe the workgroup schedulers of existing GPUs.

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