PIUMA: Programmable Integrated Unified Memory Architecture

High performance large scale graph analytics is essential to timely analyze relationships in big data sets. Conventional processor architectures suffer from inefficient resource usage and bad scaling on graph workloads. To enable efficient and scalable graph analysis, Intel developed the Programmabl...

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Main Authors Aananthakrishnan, Sriram, Ahmed, Nesreen K, Cave, Vincent, Cintra, Marcelo, Demir, Yigit, Kristof Du Bois, Eyerman, Stijn, Fryman, Joshua B, Ganev, Ivan, Heirman, Wim, Hoppe, Hans-Christian, Howard, Jason, Hur, Ibrahim, Kodiyath, MidhunChandra, Jain, Samkit, Klowden, Daniel S, Landowski, Marek M, Montigny, Laurent, More, Ankit, Ossowski, Przemyslaw, Pawlowski, Robert, Pepperling, Nick, Petrini, Fabrizio, Sikora, Mariusz, Balasubramanian Seshasayee, Smith, Shaden, Szkoda, Sebastian, Tayal, Sanjaya, Jesmin Jahan Tithi, Vandriessche, Yves, Wrosz, Izajasz P
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LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 13.10.2020
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Abstract High performance large scale graph analytics is essential to timely analyze relationships in big data sets. Conventional processor architectures suffer from inefficient resource usage and bad scaling on graph workloads. To enable efficient and scalable graph analysis, Intel developed the Programmable Integrated Unified Memory Architecture (PIUMA). PIUMA consists of many multi-threaded cores, fine-grained memory and network accesses, a globally shared address space and powerful offload engines. This paper presents the PIUMA architecture, and provides initial performance estimations, projecting that a PIUMA node will outperform a conventional compute node by one to two orders of magnitude. Furthermore, PIUMA continues to scale across multiple nodes, which is a challenge in conventional multinode setups.
AbstractList High performance large scale graph analytics is essential to timely analyze relationships in big data sets. Conventional processor architectures suffer from inefficient resource usage and bad scaling on graph workloads. To enable efficient and scalable graph analysis, Intel developed the Programmable Integrated Unified Memory Architecture (PIUMA). PIUMA consists of many multi-threaded cores, fine-grained memory and network accesses, a globally shared address space and powerful offload engines. This paper presents the PIUMA architecture, and provides initial performance estimations, projecting that a PIUMA node will outperform a conventional compute node by one to two orders of magnitude. Furthermore, PIUMA continues to scale across multiple nodes, which is a challenge in conventional multinode setups.
Author Aananthakrishnan, Sriram
Sikora, Mariusz
Szkoda, Sebastian
Howard, Jason
Hur, Ibrahim
Fryman, Joshua B
More, Ankit
Petrini, Fabrizio
Hoppe, Hans-Christian
Ganev, Ivan
Cave, Vincent
Montigny, Laurent
Vandriessche, Yves
Klowden, Daniel S
Kodiyath, MidhunChandra
Landowski, Marek M
Jain, Samkit
Ahmed, Nesreen K
Pawlowski, Robert
Ossowski, Przemyslaw
Smith, Shaden
Wrosz, Izajasz P
Heirman, Wim
Cintra, Marcelo
Kristof Du Bois
Tayal, Sanjaya
Demir, Yigit
Eyerman, Stijn
Pepperling, Nick
Balasubramanian Seshasayee
Jesmin Jahan Tithi
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