SynCron: Efficient Synchronization Support for Near-Data-Processing Architectures

Giannoula, C., Vijaykumar, N., Papadopoulou, N. , Karakostas, V., Fernandez, I., Gomez-Luna, J., Orosa, L., Koziris, N., Goumas, G. and Mutlu, O. (2021) SynCron: Efficient Synchronization Support for Near-Data-Processing Architectures. In: 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA), Seoul, South Korea, 27 Feb - 03 Mar 2021, pp. 263-273. ISBN 9781665422352 (doi: 10.1109/hpca51647.2021.00031)

Abstract

Near-Data-Processing (NDP) architectures present a promising way to alleviate data movement costs and can provide significant performance and energy benefits to parallel applications. Typically, NDP architectures support several NDP units, each including multiple simple cores placed close to memory. To fully leverage the benefits of NDP and achieve high performance for parallel workloads, efficient synchronization among the NDP cores of a system is necessary. However, supporting synchronization in many NDP systems is challenging because they lack shared caches and hardware cache coherence support, which are commonly used for synchronization in multicore systems, and communication across different NDP units can be expensive. This paper comprehensively examines the synchronization problem in NDP systems, and proposes SynCron, an end-to-end synchronization solution for NDP systems. SynCron adds low-cost hardware support near memory for synchronization acceleration, and avoids the need for hardware cache coherence support. SynCron has three components: 1) a specialized cache memory structure to avoid memory accesses for synchronization and minimize latency overheads, 2) a hierarchical message-passing communication protocol to minimize expensive communication across NDP units of the system, and 3) a hardware-only overflow management scheme to avoid performance degradation when hardware resources for synchronization tracking are exceeded. We evaluate SynCron using a variety of parallel workloads, covering various contention scenarios. SynCron improves performance by 1.27× on average (up to 1.78×) under high-contention scenarios, and by 1.35× on average (up to 2.29×) under low-contention real applications, compared to state-of-the-art approaches. SynCron reduces system energy consumption by 2.08× on average (up to 4.25×).

• Item Type: Conference Proceedings
• Additional Information: We acknowledge support from the SAFARI group’s industrial partners, especially ASML, Google, Facebook, Huawei, Intel, Microsoft, VMware, and Semiconductor Research Corporation. During part of this research, Christina Giannoula was funded from the General Secretariat for Research and Technology (GSRT) and the Hellenic Foundation for Research and Innovation (HFRI).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Papadopoulou, Dr Nikela
• Authors: Giannoula, C., Vijaykumar, N., Papadopoulou, N., Karakostas, V., Fernandez, I., Gomez-Luna, J., Orosa, L., Koziris, N., Goumas, G., and Mutlu, O.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)
• ISSN: 2378-203X
• ISBN: 9781665422352
• Copyright Holders: Copyright © 2021 IEEE
• First Published: First published in Proceedings of the 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher