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Abhishek Kulkarni

Researcher at Indiana University

Publications -  29
Citations -  236

Abhishek Kulkarni is an academic researcher from Indiana University. The author has contributed to research in topics: Biology & Scalability. The author has an hindex of 7, co-authored 20 publications receiving 187 citations. Previous affiliations of Abhishek Kulkarni include Intel & Los Alamos National Laboratory.

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Proceedings ArticleDOI

Using simulation to explore distributed key-value stores for extreme-scale system services

TL;DR: This paper simulates KVS for various service architectures and examines the design trade-offs as applied to HPC service workloads to support extreme-scale systems, and demonstrates how failure, replication, and consistency models affect performance at scale.
Journal ArticleDOI

An In Vivo Zebrafish Model for Interrogating ROS-Mediated Pancreatic β-Cell Injury, Response, and Prevention.

TL;DR: In this paper, the authors used a zebrafish model to demonstrate that reactive oxygen species (ROS) can be generated in a β-cell-specific manner using a hybrid chemical genetic approach.
Proceedings ArticleDOI

A meta-scheduler for the par-monad: composable scheduling for the heterogeneous cloud

TL;DR: This work proposes a general, composable abstraction for execution resources, along with a continuation-based meta-scheduler that harnesses those resources in the context of a deterministic parallel programming library for Haskell, and demonstrates performance benefits of combined CPU/GPU scheduling over either alone or alone.
Book ChapterDOI

Concurrent Cilk: Lazy Promotion from Tasks to Threads in C/C++

TL;DR: An extension to the Intel Cilk Plus runtime system, Concurrent Cilk, is described, where tasks are lazily promoted to threads, and is the first system to do so for C/C++ with legacy support standard calling conventions and stack representations.
Journal ArticleDOI

Exploring the Design Tradeoffs for Extreme-Scale High-Performance Computing System Software

TL;DR: A general system software taxonomy is proposed by deconstructing common HPC system software into their basic components and it is envisioned that the results in this article help to lay the foundations of developing next-generation HPCSystem software for extreme scales.