23 citations · 26 across the 6 of their papers we have counts for
6 papers
PIM-LLM: A High-Throughput Hybrid PIM Architecture for 1-bit LLMs
Jinendra Malekar, Peyton Chandarana, Md Hasibul Amin +2
In this paper, we propose PIM-LLM, a hybrid architecture developed to accelerate 1-bit large language models (LLMs). PIM-LLM leverages analog processing-in-memory (PIM) architectur…
Towards Efficient Deployment of Hybrid SNNs on Neuromorphic and Edge AI Hardware
James Seekings, Peyton Chandarana, Mahsa Ardakani +2
This paper explores the synergistic potential of neuromorphic and edge computing to create a versatile machine learning (ML) system tailored for processing data captured by dynamic…
Flex-TPU: A Flexible TPU with Runtime Reconfigurable Dataflow Architecture
Mohammed Elbtity, Peyton Chandarana, Ramtin Zand
Tensor processing units (TPUs) are one of the most well-known machine learning (ML) accelerators utilized at large scale in data centers as well as in tiny ML applications. TPUs of…
Energy-Efficient Deployment of Machine Learning Workloads on Neuromorphic Hardware
Peyton Chandarana, Mohammadreza Mohammadi, James Seekings +1
As the technology industry is moving towards implementing tasks such as natural language processing, path planning, image classification, and more on smaller edge computing devices…
Static Hand Gesture Recognition for American Sign Language using Neuromorphic Hardware
MohammadReza Mohammadi, Peyton Chandarana, James Seekings +2
In this paper, we develop four spiking neural network (SNN) models for two static American Sign Language (ASL) hand gesture classification tasks, i.e., the ASL Alphabet and ASL Dig…
An Adaptive Sampling and Edge Detection Approach for Encoding Static Images for Spiking Neural Networks
Peyton Chandarana, Junlin Ou, Ramtin Zand
Current state-of-the-art methods of image classification using convolutional neural networks are often constrained by both latency and power consumption. This places a limit on the…