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DTSTART:19700308T020000
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DTSTAMP:20220715T000418Z
LOCATION:3002\, Level 3
DTSTART;TZID=America/Los_Angeles:20220713T155400
DTEND;TZID=America/Los_Angeles:20220713T161800
UID:dac_DAC 2022_sess128_RESEARCH936@linklings.com
SUMMARY:Improving Compute In-Memory ECC Reliability with Successive Correc
 tion
DESCRIPTION:Research Manuscript\n\nImproving Compute In-Memory ECC Reliabi
 lity with Successive Correction\n\nCrafton, Wan, Spetalnick, Yoon, Wu...\n
 \nCompute in-memory is an exciting technique that minimizes data transport
 , maximizes memory throughput, and performs computation on the bitline of 
 memory sub-arrays. This is especially interesting for machine learning app
 lications, where increased memory bandwidth and analog domain computation 
 offer improved area and energy efficiency. In this work, we explore the im
 pact of device variation (calibrated with measured data) and propose a new
  class of ECC for CIM. We demonstrate single, double, and triple error cor
 rection offering up to 16,000x reduction in BER over no ECC and over 33x o
 ver prior work, while consuming only 29.1% area and 26.3% power overhead.\
 n\nTopic: Design\n\nKeyword: Emerging Device Technologies
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