Recent Trends in Leveraging Processing-in-Memory for Accelerating Relational Database Management Systems
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In this paper, we present a comprehensive survey on recent research exploiting Processing-In-Memory (PIM) to enhance the performanceof Relational Database Management Systems (RDBMSs). PIM integrates In-Memory Processors (IMPs) near memory banks, allowingmemory-intensive operations to leverage the high internal memory bandwidth and computational capabilities of IMPs. Given that manykey operations of RDBMSs are memory-heavy and require a large number of frequent memory accesses, PIM has emerged as a promisingsolution for accelerating RDBMSs. We provide an overview of the key architectural characteristics of commodity PIM-enabled memorydevices, examine how recent studies have applied PIM to accelerate RDBMSs, and explore potential research directions in PIM-acceleratedRDBMSs.
Abstract
In this paper, we present a comprehensive survey on recent research exploiting Processing-In-Memory (PIM) to enhance the performanceof Relational Database Management Systems (RDBMSs). PIM integrates In-Memory Processors (IMPs) near memory banks, allowingmemory-intensive operations to leverage the high internal memory bandwidth and computational capabilities of IMPs. Given that manykey operations of RDBMSs are memory-heavy and require a large number of frequent memory accesses, PIM has emerged as a promisingsolution for accelerating RDBMSs. We provide an overview of the key architectural characteristics of commodity PIM-enabled memorydevices, examine how recent studies have applied PIM to accelerate RDBMSs, and explore potential research directions in PIM-acceleratedRDBMSs.
참고문헌 (22)
- C. J. Date, "A guide to the SQL standard" (1989), Addison-Wesley Longman Publishing Co., Inc
- A. Boroumand, "Polynesia : Enabling high-performance and energyefficient hybrid transactional", analytical databases with hardware, IEEE 38th International Conference on Data Engineering(ICDE), pp.2022[DOI]
- S. I. F. G. N. Nes, "MonetDB : Two decades of research in column-oriented database architectures", Data Engineering, 40 (2012)
- S. R. dos Santos, "Advancing Database System Operators with Near-Data Processing", 2022 30th Euromicro International Conference on Parallel, Distributed and Network-based Processing(PDP) (2022)
- S. K. Begley, "Mcjoin : A memory-constrained join for column-store main-memory databases", Proceedings of the ACM SIGMOD International Conference on Management of Data (2012)
- H. Gao, "Scaling Joins to a Thousand GPUs", ADMS@ VLDB (2021)
- P. Chi, "Prime : A novel processing-in-memory architecture for neural network computation in rerambased main memory", ACM SIGARCH Computer Architecture News, 44 (2016)
- A. Shafiee, "ISAAC : A convolutional neural network accelerator with in-situ analog arithmetic in crossbars", ACM SIGARCH Computer Architecture News, 44(3), pp.14~26 (2016)
- M. Imani, "Floatpim : In-memory acceleration of deep neural network training with high precision", Proceedings of the 46th International Symposium on Computer Architecture (2019)
- F. Zhang, "Pim-quantifier : A processing-in-memory platform for mrna quantification", 2021 58th ACM, 2021, ~
- S. Angizi, "Pimassembler : A processing-in-memory platform for genome assembly", 2020 57th ACM, 2020, ~
- S. Angizi, "PIM-Aligner : A processing-in-MRAM platform for biological sequence alignment", 2020 Design, Automation & Test in Europe Conference & Exhibition(DATE) (2020)
- L. Ke, "Near-memory processing in action : Accelerating personalized recommendation with axdimm", IEEE Micro, 42 (2021)
- M. He, "Newton: A DRAM-maker’s accelerator-inmemory (AiM) architecture for machine learning", 53rd Annual IEEE, 2020, ~
- S. Lee, "Hardware architecture and software stack for PIM based on commercial DRAM technology: Industrial product", ACM, 2021, ~
- F. Devaux, "The true processing in memory accelerator", IEEE Hot Chips 31 Symposium(HCS) (2019)
- J. H. Kim, "Aquabolt-XL : Samsung HBM2-PIM with in-memory processing for ML accelerators and beyond", IEEE Hot Chips 33 Symposium(HCS) (2021)
- J. H. Kim, "Aquabolt-XL HBM2-PIM, LPDDR5-PIM with in-memory processing, and AXDIMM with acceleration buffer", IEEE Micro, 42 (2022)
- B. Alexander, "Accelerating large table scans using processing-in-memory technology", Proceedings of the 20th Conference on Database Systems for Business, Technology and Web(BTW) (2023)
- B. Alexander, "Processingin-memory for databases : Query processing and data transfer", Proceedings of the 19th International Workshop on Data Management on New Hardware(DaMoN) (2023)
- "UPMEMPIM Evaluation for SQL Query Acceleration"[URL]
- C. Lim, "DIMM Join Algorithm : A Case Study with UPMEM DIMMs", Proceedings of the 2023 ACM SIGMOD International Conference on Management of Data (SIGMOD) (2023)