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20162025
most citedAI and ML Accelerator Survey and Trends

96 citations · 213 across the 21 of their papers we have counts for

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8 papers · 1 filter

cs.DB20213 cited

Technical Report on Data Integration and Preparation

El Kindi Rezig, Michael Cafarella, Vijay Gadepally

AI application developers typically begin with a dataset of interest and a vision of the end analytic or insight they wish to gain from the data at hand. Although these are two ver…

cs.DB20201 cited

Technical Report: Developing a Working Data Hub

Vijay Gadepally, Jeremy Kepner

Data forms a key component of any enterprise. The need for high quality and easy access to data is further amplified by organizations wishing to leverage machine learning or artifi…

cs.DB20204 cited

AI Data Wrangling with Associative Arrays

Jeremy Kepner, Vijay Gadepally, Hayden Jananthan +2

The AI revolution is data driven. AI "data wrangling" is the process by which unusable data is transformed to support AI algorithm development (training) and deployment (inference)…

cs.DB2019

RedisGraph GraphBLAS Enabled Graph Database

Pieter Cailliau, Tim Davis, Vijay Gadepally +4

RedisGraph is a Redis module developed by Redis Labs to add graph database functionality to the Redis database. RedisGraph represents connected data as adjacency matrices. By repre…

cs.DB20195 cited

A Billion Updates per Second Using 30,000 Hierarchical In-Memory D4M Databases

Jeremy Kepner, Vijay Gadepally, Lauren Milechin +15

Analyzing large scale networks requires high performance streaming updates of graph representations of these data. Associative arrays are mathematical objects combining properties…

cs.DB2018

Database Operations in D4M.jl

Lauren Milechin, Vijay Gadepally, Jeremy Kepner

Each step in the data analytics pipeline is important, including database ingest and query. The D4M-Accumulo database connector has allowed analysts to quickly and easily ingest to…