Digital-based Processing In-Memory: A Highly-Parallel Accelerator for Data Intensive Applications

被引:2
|
作者
Imani, Mohsen [1 ]
Gupta, Saransh [1 ]
Rosing, Tajana [1 ]
机构
[1] Univ Calif San Diego, Dept Comp Sci & Engn, La Jolla, CA 92093 USA
来源
MEMSYS 2019: PROCEEDINGS OF THE INTERNATIONAL SYMPOSIUM ON MEMORY SYSTEMS | 2019年
关键词
Processing in-memory; Non-volatile memory; Machine learning acceleration;
D O I
10.1145/3357526.3357551
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Recently, Processing In-Memory (PIM) has been shown as a promising solution to address data movement issue in the current processors. However, today's PIM technologies are mostly analog-based, which involve both scalability and efficiency issues. In this paper, we propose a novel digital-based PIM which accelerates fundamental operations and diverse data analytic procedures using processing in-memory technology. Instead of sending a large amount of data to the processing cores for computation, our design performs a large part of computation tasks inside the memory; thus the application performance can be accelerated significantly by avoiding the memory access bottleneck. Digital-based PIM supports bit-wise operations between two selected bit-line of the memory block and then extends it to support row-parallel arithmetic operations.
引用
收藏
页码:38 / 40
页数:3
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