Maximizing GPU Parallelism for a High-performance Cryptanalysis System

Modern cryptanalysis techniques utilize GPUs, owing to their parallel processing power, to significantly improve the speed of cryptanalysis tasks. Thus, recent research directions have focused on maximizing parallelism to complete large-scale cryptanalysis in a short time. For this, previous works u...

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Bibliographic Details
Published in:International Conference on Information Networking (Online) pp. 572 - 577
Main Authors: Kim, Sangyub, Shin, Youngjoo
Format: Conference Proceeding
Language:English
Published: IEEE 15.01.2025
Subjects:
Cryptanalysis System
Data processing
Graphics processing units
Kernel
Multi-Instance GPU
Multi-Process Service
Parallel Computing
Parallel processing
ISSN:2996-1580
Online Access:Get full text
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Summary:Modern cryptanalysis techniques utilize GPUs, owing to their parallel processing power, to significantly improve the speed of cryptanalysis tasks. Thus, recent research directions have focused on maximizing parallelism to complete large-scale cryptanalysis in a short time. For this, previous works utilized NVIDIA's technologies such as Hyper-Q, Multi-Process Service (MPS), and Multi-Instance GPU (MIG) for their cryptanalysis system. However, no effort has been made to evaluate whether integrating these technologies improves parallelism compared to a single one. In this paper, we design and implement a cryptanalysis system that integrates MPS and MIG. To evaluate this system, we develop three versions of Strassen's matrix multiplication programs for large-scale cryptanalysis. We evaluate the performance of these programs using CUDA, cuBLAS, and a combination of cuBLAS and MPI, respectively. Our results show that with both MPS and MIG enabled, the computation time for matrix multiplication is approximately 1.42×, 1.28×, and 2.02× faster.
ISSN:2996-1580
DOI:10.1109/ICOIN63865.2025.10993057