Max-PIM: Fast and Efficient Max/Min Searching in DRAM
Recently, in-DRAM computing is becoming one promising technique to address the notorious 'memory-wall' issue for big data processing. In this work, for the first time, we propose a novel 'Min/Max-in-memory' algorithm based on iterative XNOR bit-wise comparison, which supports par...
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| Vydáno v: | 2021 58th ACM/IEEE Design Automation Conference (DAC) s. 211 - 216 |
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05.12.2021
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| Abstract | Recently, in-DRAM computing is becoming one promising technique to address the notorious 'memory-wall' issue for big data processing. In this work, for the first time, we propose a novel 'Min/Max-in-memory' algorithm based on iterative XNOR bit-wise comparison, which supports parallel inmemory searching for minimum and maximum of bulk data stored in DRAM as unsigned & signed integers, fixed-point and floating numbers. We then develop a new processing-in-DRAM architecture, called Max-PIM, that supports complete bit-wise Boolean logic and beyond. Differentiating from prior works, Max-PIM is optimized with one-cycle fast XNOR logicin-DRAM operation and in-memory data transpose, which are heavily used and keys to accelerate the proposed Min/Max-in-memory algorithm efficiently. Extensive experiments of utilizing Max-PIM in big data sorting and graph processing applications show that it could speed up ~ 50X and ~ 1000X than GPU and CPU, while only consuming 10% and 1% energy, respectively. Moreover, comparing with recent representative In-DRAM computing platforms, i.e., Ambit [1], DRISA [2], our design could speed up ~ 3X - 10X. |
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| AbstractList | Recently, in-DRAM computing is becoming one promising technique to address the notorious 'memory-wall' issue for big data processing. In this work, for the first time, we propose a novel 'Min/Max-in-memory' algorithm based on iterative XNOR bit-wise comparison, which supports parallel inmemory searching for minimum and maximum of bulk data stored in DRAM as unsigned & signed integers, fixed-point and floating numbers. We then develop a new processing-in-DRAM architecture, called Max-PIM, that supports complete bit-wise Boolean logic and beyond. Differentiating from prior works, Max-PIM is optimized with one-cycle fast XNOR logicin-DRAM operation and in-memory data transpose, which are heavily used and keys to accelerate the proposed Min/Max-in-memory algorithm efficiently. Extensive experiments of utilizing Max-PIM in big data sorting and graph processing applications show that it could speed up ~ 50X and ~ 1000X than GPU and CPU, while only consuming 10% and 1% energy, respectively. Moreover, comparing with recent representative In-DRAM computing platforms, i.e., Ambit [1], DRISA [2], our design could speed up ~ 3X - 10X. |
| Author | Angizi, Shaahin Zhang, Fan Fan, Deliang |
| Author_xml | – sequence: 1 givenname: Fan surname: Zhang fullname: Zhang, Fan email: fzhang95@asu.edu organization: Arizona State University,School of Electrical, Computer and Energy Engineering,Tempe,USA – sequence: 2 givenname: Shaahin surname: Angizi fullname: Angizi, Shaahin email: sangizi@asu.edu organization: Arizona State University,School of Electrical, Computer and Energy Engineering,Tempe,USA – sequence: 3 givenname: Deliang surname: Fan fullname: Fan, Deliang email: dfan@asu.edu organization: Arizona State University,School of Electrical, Computer and Energy Engineering,Tempe,USA |
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| Snippet | Recently, in-DRAM computing is becoming one promising technique to address the notorious 'memory-wall' issue for big data processing. In this work, for the... |
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| SubjectTerms | Big Data Design automation Graphics processing units IMC In-DRAM Computing Iterative algorithms Memory management Min/Max Parallel processing PIM Random access memory |
| Title | Max-PIM: Fast and Efficient Max/Min Searching in DRAM |
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