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Computer Science > Hardware Architecture

arXiv:2503.20481 (cs)
[Submitted on 26 Mar 2025]

Title:Analyzing Modern NVIDIA GPU cores

Authors:Rodrigo Huerta, Mojtaba Abaie Shoushtary, Jose-Lorenzo Cruz,
Antonio Gonzalez
View a PDF of the paper titled Analyzing Modern NVIDIA GPU cores, by
Rodrigo Huerta and 3 other authors
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    Abstract:GPUs are the most popular platform for accelerating HPC
    workloads, such as artificial intelligence and science
    simulations. However, most microarchitectural research in
    academia relies on GPU core pipeline designs based on
    architectures that are more than 15 years old.
    This paper reverse engineers modern NVIDIA GPU cores, unveiling
    many key aspects of its design and explaining how GPUs leverage
    hardware-compiler techniques where the compiler guides hardware
    during execution. In particular, it reveals how the issue logic
    works including the policy of the issue scheduler, the structure
    of the register file and its associated cache, and multiple
    features of the memory pipeline. Moreover, it analyses how a
    simple instruction prefetcher based on a stream buffer fits well
    with modern NVIDIA GPUs and is likely to be used. Furthermore, we
    investigate the impact of the register file cache and the number
    of register file read ports on both simulation accuracy and
    performance.
    By modeling all these new discovered microarchitectural details,
    we achieve 18.24% lower mean absolute percentage error (MAPE) in
    execution cycles than previous state-of-the-art simulators,
    resulting in an average of 13.98% MAPE with respect to real
    hardware (NVIDIA RTX A6000). Also, we demonstrate that this new
    model stands for other NVIDIA architectures, such as Turing.
    Finally, we show that the software-based dependence management
    mechanism included in modern NVIDIA GPUs outperforms a hardware
    mechanism based on scoreboards in terms of performance and area.

Subjects: Hardware Architecture (cs.AR)
Cite as:  arXiv:2503.20481 [cs.AR]
          (or arXiv:2503.20481v1 [cs.AR] for this version)
          https://doi.org/10.48550/arXiv.2503.20481
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Rodrigo Huerta [view email]
[v1] Wed, 26 Mar 2025 12:10:53 UTC (246 KB)
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