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Conference Paper Design and Implementation of Data-Intensive Application using Memory Expansion Device
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Authors
HooYoung Ahn, SeonYoung Kim, Yoo-mi Park, Woo-Jong Han
Issue Date
2023-10
Citation
International Conference on Information and Communication Technology Convergence (ICTC) 2023, pp.1776-1780
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICTC58733.2023.10393143
Abstract
Modern intelligent applications utilizing data-driven analysis have gained significant attention. As these applications rely on analyzing large-scale data for improved performance, they demand substantial high-performance memory. However, current computer architectures often lack the capacity to provide enough fast memory, leading to performance degradation in such applications. To address these limitations, memory expansion devices are being developed that connect to host servers through the new cache coherent interconnects like CXL. These devices offer additional memory and hardware acceleration capabilities to enhance performance.In this paper, we propose a novel method to accelerate data-intensive MPI applications in a CPU-FPGA heterogeneous computing environment, employing memory expansion devices called MEX. Our approach leverages MEX and MPI to enable near-memory processing by utilizing MEX as shared computing resources. To the best of our knowledge, this is the first study to combine memory expansion devices and MPI for accelerating data-intensive MPI applications. We implement a content-based image similarity search system using MPI and MEX and verify the feasibility of our proposed methods.
KSP Keywords
CPU-FPGA, Cache Coherent, Computer Architecture, Computing environment, Data intensive applications, Enhance performance, Expansion device, Heterogeneous computing, High performance, Image similarity search, Large-scale data