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M. Ali

3 papers hereh-index 13766 citations20 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.AR1
  • cs.ET1
  • cs.LG1
same name
  • M. Ali — 10 papers
  • M. Ali — 9 papers, h 50
  • M. Ali — 5 papers, h 17
  • M. Ali — 3 papers, h 18
  • M. Ali — 3 papers, h 26
  • M. Ali — 2 papers, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedIMPULSE: A 65nm Digital Compute-in-Memory Macro with Fused Weights and Membrane Potential for Spike-based Sequential Learning Tasks

47 citations · 47 across the 1 of their papers we have counts for

collaborators

3 papers

cs.AR2021★ 47 cited

IMPULSE: A 65nm Digital Compute-in-Memory Macro with Fused Weights and Membrane Potential for Spike-based Sequential Learning Tasks

Amogh Agrawal, Mustafa Ali, Minsuk Koo +3

The inherent dynamics of the neuron membrane potential in Spiking Neural Networks (SNNs) allows processing of sequential learning tasks, avoiding the complexity of recurrent neural…

cs.LG2021

PIM-DRAM: Accelerating Machine Learning Workloads using Processing in Commodity DRAM

Sourjya Roy, Mustafa Ali, Anand Raghunathan

Deep Neural Networks (DNNs) have transformed the field of machine learning and are widely deployed in many applications involving image, video, speech and natural language processi…

cs.ET2020

IMAC: In-memory multi-bit Multiplication andACcumulation in 6T SRAM Array

Mustafa Ali, Akhilesh Jaiswal, Sangamesh Kodge +3

`In-memory computing' is being widely explored as a novel computing paradigm to mitigate the well known memory bottleneck. This emerging paradigm aims at embedding some aspects of…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.