Scalability Limitations of Processing-in-Memory using Real System Evaluations

被引：0

作者：

Jonatan G. ^{[1
]}

Cho H. ^{[1
]}

Son H. ^{[1
]}

Wu X. ^{[1
]}

Livesay N. ^{[2
]}

Mora E. ^{[3
]}

Shivdikar K. ^{[2
]}

Abellán J.L. ^{[4
]}

Joshi A. ^{[5
]}

Kaeli D. ^{[2
]}

Kim J. ^{[1
]}

机构：

[1] Universidad Católica de Murcia, Murcia

[2] Universidad de Murcia, Murcia

[3] Boston University, Boston

来源：

Performance Evaluation Review | 2024年 / 52卷 / 01期

关键词：

collective communication; interconnection networks; processing-in-memory;

D O I：

10.1145/3673660.3655079

中图分类号：

学科分类号：

摘要：

Processing-in-memory (PIM) has been widely explored in academia and industry to accelerate numerous workloads. By reducing the data movement and increasing parallelism, PIM offers great performance and energy efficiency. A large amount of cores or nodes present in PIM provide massive parallelism and compute throughput; however, this also proposes challenges and limitations for some workloads. In this work, we provide an extensive evaluation and analysis of a real PIM system from UPMEM. We specifically target emerging workloads featuring collective communication, demonstrating its role as the primary limitation within current PIM architecture. © 2024 Owner/Author.

引用

页码：63 / 64

页数：1

共 5 条

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