pLUTo: Enabling Massively Parallel Computation in DRAM via Lookup Tables

Joao Dinis Ferreira, Gabriel Falcao, Juan Gomez-Luna, Mohammed Alser, Lois Orosa, Mohammad Sadrosadati, Jeremie S. Kim, Geraldo F. Oliveira, Taha Shahroodi, More Authors

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

6 Citations (Scopus)
23 Downloads (Pure)

Abstract

Data movement between the main memory and the processor is a key contributor to execution time and energy consumption in memory-intensive applications. This data movement bottleneck can be alleviated using Processing-in-Memory (PiM). One category of PiM is Processing-using-Memory (PuM), in which computation takes place inside the memory array by exploiting intrinsic analog properties of the memory device. PuM yields high performance and energy efficiency, but existing PuM techniques support a limited range of operations. As a result, current PuM architectures cannot efficiently perform some complex operations (e.g., multiplication, division, exponentiation) without large increases in chip area and design complexity. To overcome these limitations of existing PuM architectures, we introduce pLUTo (processing-using-memory with lookup table (LUT) operations), a DRAM-based PuM architecture that leverages the high storage density of DRAM to enable the massively parallel storing and querying of lookup tables (LUTs). The key idea of pLUTo is to replace complex operations with low-cost, bulk memory reads (i.e., LUT queries) instead of relying on complex extra logic. We evaluate pLUTo across 11 real-world workloads that showcase the limitations of prior PuM approaches and show that our solution outperforms optimized CPU and GPU base-lines by an average of 713 × and 1.2 ×, respectively, while simultaneously reducing energy consumption by an average of 1855 × and 39.5 ×. Across these workloads, pLUTo outperforms state-of-the-art PiM architectures by an average of 18.3 ×. We also show that different versions of pLUTo provide different levels of flexibility and performance at different additional DRAM area overheads (between 10.2% and 23.1%). pLUTo's source code and all scripts required to reproduce the results of this paper are openly and fully available at https://github.com/CMU-SAFARI/pLUTo.

Original languageEnglish
Title of host publicationProceedings - 2022 55th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2022
PublisherIEEE
Pages900-919
Number of pages20
ISBN (Electronic)978-1-6654-6272-3
DOIs
Publication statusPublished - 2022
Event55th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2022 - Chicago, United States
Duration: 1 Oct 20225 Oct 2022

Publication series

NameProceedings of the Annual International Symposium on Microarchitecture, MICRO
Volume2022-October
ISSN (Print)1072-4451

Conference

Conference55th Annual IEEE/ACM International Symposium on Microarchitecture, MICRO 2022
Country/TerritoryUnited States
CityChicago
Period1/10/225/10/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

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