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arXiv · 2501.00210

Debunking the CUDA Myth Towards GPU-based AI Systems

Yunjae Lee·Juntaek Lim·Jehyeon Bang·Eunyeong Cho·Huijong Jeong·Taesu Kim·Hyungjun Kim·Joonhyung Lee·Jinseop Im·Ranggi Hwang·Se Jung Kwon·Dongsoo Lee·Minsoo Rhu
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Abstract

This paper presents a comprehensive evaluation of Intel Gaudi NPUs as an alternative to NVIDIA GPUs, which is currently the de facto standard in AI system design. First, we create a suite of microbenchmarks to compare Intel Gaudi-2 with NVIDIA A100, showing that Gaudi-2 achieves competitive performance not only in primitive AI compute, memory, and communication operations but also in executing several important AI workloads end-to-end. We then assess Gaudi NPU's programmability by discussing several software-level optimization strategies to employ for implementing critical FBGEMM operators and vLLM, evaluating their efficiency against GPU-optimized counterparts. Results indicate that Gaudi-2 achieves energy efficiency comparable to A100, though there are notable areas for improvement in terms of software maturity. Overall, we conclude that, with effective integration into high-level AI frameworks, Gaudi NPUs could challenge NVIDIA GPU's dominance in the AI server market, though further improvements are necessary to fully compete with NVIDIA's robust software ecosystem.

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Yunjae Lee, Juntaek Lim, Jehyeon Bang, Eunyeong Cho, Huijong Jeong, Taesu Kim, Hyungjun Kim, Joonhyung Lee, Jinseop Im, Ranggi Hwang, Se Jung Kwon, Dongsoo Lee, Minsoo Rhu. 2025-03-22. Debunking the CUDA Myth Towards GPU-based AI Systems. https://arxiv.org/abs/2501.00210

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