Triton-Viz: Visualizing GPU Programming in AI Courses

GPU programming is a critical component in AI system courses, which is notoriously difficult to learn and teach, given its unique features such as massive parallelism and data movement across memory hierarchies. This paper presents Triton-Viz, an innovative visualization toolkit that helps students learn GPU programming using Triton, one of the most widely used programming languages to develop AI applications. Triton-Viz offers an intuitive interface with interactive visualizations of GPU operations from multiple perspectives, including parallelism, memory access, and performance metrics. By integrating into educational materials, Triton-Viz enhances hands-on learning and improves comprehension of GPU programming concepts and AI algorithms in real applications, as demonstrated in a study conducted with Computer Science students. The positive feedback from this study highlights the utility of Triton-Viz in educational settings and its potential to bridge the gap between the theoretical algorithm and practical implementations in AI courses.

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Publication Details

Published
2025-02-12
DOI
https://doi.org/10.1145/3641554.3701795
Primary Topic
Teaching and Learning Programming
Type
article
Field-Weighted Citation Impact
0.00

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article

Triton-Viz: Visualizing GPU Programming in AI Courses

Binqian Yin, Xu Liu, T. Ramesh, Alexander M. Rush et al.
Teaching and Learning Programming
article

Triton-Viz: Visualizing GPU Programming in AI Courses

Binqian Yin, Xu Liu, T. Ramesh, Alexander M. Rush, Keren Zhou, Shuyin Jiao
article en

Abstract

GPU programming is a critical component in AI system courses, which is notoriously difficult to learn and teach, given its unique features such as massive parallelism and data movement across memory hierarchies. This paper presents Triton-Viz, an innovative visualization toolkit that helps students learn GPU programming using Triton, one of the most widely used programming languages to develop AI applications. Triton-Viz offers an intuitive interface with interactive visualizations of GPU operations from multiple perspectives, including parallelism, memory access, and performance metrics. By integrating into educational materials, Triton-Viz enhances hands-on learning and improves comprehension of GPU programming concepts and AI algorithms in real applications, as demonstrated in a study conducted with Computer Science students. The positive feedback from this study highlights the utility of Triton-Viz in educational settings and its potential to bridge the gap between the theoretical algorithm and practical implementations in AI courses.

North Carolina State University (US), George Mason University (US), Cornell University (US)
National Science Foundation
Openalex Percentile: Top 98%
Teaching and Learning Programming
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