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Fine‐Grained Memory Profiling of GPGPU Kernels

Buelow, Max von ; Guthe, Stefan ; Fellner, Dieter W. (2023)
Fine‐Grained Memory Profiling of GPGPU Kernels.
In: Computer Graphics Forum, 2023, 41 (7)
doi: 10.26083/tuprints-00023702
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Fine‐Grained Memory Profiling of GPGPU Kernels
Language: English
Date: 10 November 2023
Place of Publication: Darmstadt
Year of primary publication: 2023
Place of primary publication: Oxford
Publisher: Wiley-Blackwell
Journal or Publication Title: Computer Graphics Forum
Volume of the journal: 41
Issue Number: 7
DOI: 10.26083/tuprints-00023702
Corresponding Links:
Origin: Secondary publication DeepGreen

Memory performance is a crucial bottleneck in many GPGPU applications, making optimizations for hardware and software mandatory. While hardware vendors already use highly efficient caching architectures, software engineers usually have to organize their data accordingly in order to efficiently make use of these, requiring deep knowledge of the actual hardware. In this paper we present a novel technique for fine‐grained memory profiling that simulates the whole pipeline of memory flow and finally accumulates profiling values in a way that the user retains information about the potential region in the GPU program by showing these values separately for each allocation. Our memory simulator turns out to outperform state‐of‐the‐art memory models of NVIDIA architectures by a magnitude of 2.4 for the L1 cache and 1.3 for the L2 cache, in terms of accuracy. Additionally, we find our technique of fine grained memory profiling a useful tool for memory optimizations, which we successfully show in case of ray tracing and machine learning applications.

Uncontrolled Keywords: CCS Concepts, Hardware → Simulation and emulation, Computing methodologies → Graphics processors, Theory of computation → Program analysis
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-237027
Classification DDC: 000 Generalities, computers, information > 004 Computer science
Divisions: 20 Department of Computer Science > Interactive Graphics Systems
Date Deposited: 10 Nov 2023 15:05
Last Modified: 21 Nov 2023 08:42
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/23702
PPN: 513343989
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