Search Results for author: Vivek Seshadri

Found 8 papers, 4 papers with code

MinUn: Accurate ML Inference on Microcontrollers

no code implementations29 Oct 2022 Shikhar Jaiswal, Rahul Kiran Kranti Goli, Aayan Kumar, Vivek Seshadri, Rahul Sharma

Running machine learning inference on tiny devices, known as TinyML, is an emerging research area.

Annotated Speech Corpus for Low Resource Indian Languages: Awadhi, Bhojpuri, Braj and Magahi

no code implementations26 Jun 2022 Ritesh Kumar, Siddharth Singh, Shyam Ratan, Mohit Raj, Sonal Sinha, Bornini Lahiri, Vivek Seshadri, Kalika Bali, Atul Kr. Ojha

In this paper we discuss an in-progress work on the development of a speech corpus for four low-resource Indo-Aryan languages -- Awadhi, Bhojpuri, Braj and Magahi using the field methods of linguistic data collection.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

MAFIA: Machine Learning Acceleration on FPGAs for IoT Applications

no code implementations8 Jul 2021 Nikhil Pratap Ghanathe, Vivek Seshadri, Rahul Sharma, Steve Wilton, Aayan Kumar

Recent breakthroughs in ML have produced new classes of models that allow ML inference to run directly on milliwatt-powered IoT devices.

BIG-bench Machine Learning

PipeDream: Fast and Efficient Pipeline Parallel DNN Training

1 code implementation8 Jun 2018 Aaron Harlap, Deepak Narayanan, Amar Phanishayee, Vivek Seshadri, Nikhil Devanur, Greg Ganger, Phil Gibbons

PipeDream is a Deep Neural Network(DNN) training system for GPUs that parallelizes computation by pipelining execution across multiple machines.

Distributed, Parallel, and Cluster Computing

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