Dipti Shankar

According to our database1, Dipti Shankar authored at least 24 papers between 2014 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2020
RDMP-KV: designing remote direct memory persistence based key-value stores with PMEM.
Proceedings of the International Conference for High Performance Computing, 2020

2019
SimdHT-Bench: Characterizing SIMD-Aware Hash Table Designs on Emerging CPU Architectures.
Proceedings of the IEEE International Symposium on Workload Characterization, 2019

UMR-EC: A Unified and Multi-Rail Erasure Coding Library for High-Performance Distributed Storage Systems.
Proceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing, 2019

SCOR-KV: SIMD-Aware Client-Centric and Optimistic RDMA-Based Key-Value Store for Emerging CPU Architectures.
Proceedings of the 26th IEEE International Conference on High Performance Computing, 2019

2018
MR-Advisor: A comprehensive tuning, profiling, and prediction tool for MapReduce execution frameworks on HPC clusters.
J. Parallel Distributed Comput., 2018

High-Performance Multi-Rail Erasure Coding Library over Modern Data Center Architectures: Early Experiences.
Proceedings of the ACM Symposium on Cloud Computing, 2018

Spark-uDAPL: Cost-Saving Big Data Analytics on Microsoft Azure Cloud with RDMA Networks<sup>*</sup>.
Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017
Scalable and Distributed Key-Value Store-based Data Management Using RDMA-Memcached.
IEEE Data Eng. Bull., 2017

High-Performance and Resilient Key-Value Store with Online Erasure Coding for Big Data Workloads.
Proceedings of the 37th IEEE International Conference on Distributed Computing Systems, 2017

Performance characterization and acceleration of big data workloads on OpenPOWER system.
Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

2016
Characterizing and benchmarking stand-alone Hadoop MapReduce on modern HPC clusters.
J. Supercomput., 2016

MR-Advisor: A Comprehensive Tuning Tool for Advising HPC Users to Accelerate MapReduce Applications on Supercomputers.
Proceedings of the 28th International Symposium on Computer Architecture and High Performance Computing, 2016

High-Performance Hybrid Key-Value Store on Modern Clusters with RDMA Interconnects and SSDs: Non-blocking Extensions, Designs, and Benefits.
Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium, 2016

Impact of HPC Cloud Networking Technologies on Accelerating Hadoop RPC and HBase.
Proceedings of the 2016 IEEE International Conference on Cloud Computing Technology and Science, 2016

Boldio: A hybrid and resilient burst-buffer over lustre for accelerating big data I/O.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

High-performance design of apache spark with RDMA and its benefits on various workloads.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015
Can RDMA benefit online data processing workloads on memcached and MySQL?
Proceedings of the 2015 IEEE International Symposium on Performance Analysis of Systems and Software, 2015

Accelerating I/O Performance of Big Data Analytics on HPC Clusters through RDMA-Based Key-Value Store.
Proceedings of the 44th International Conference on Parallel Processing, 2015

Triple-H: A Hybrid Approach to Accelerate HDFS on HPC Clusters with Heterogeneous Storage Architecture.
Proceedings of the 15th IEEE/ACM International Symposium on Cluster, 2015

A Plugin-Based Approach to Exploit RDMA Benefits for Apache and Enterprise HDFS.
Proceedings of the Big Data Benchmarks, Performance Optimization, and Emerging Hardware, 2015

Benchmarking key-value stores on high-performance storage and interconnects for web-scale workloads.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

Performance characterization and acceleration of in-memory file systems for Hadoop and Spark applications on HPC clusters.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014
A Micro-benchmark Suite for Evaluating Hadoop MapReduce on High-Performance Networks.
Proceedings of the Big Data Benchmarks, Performance Optimization, and Emerging Hardware, 2014

Accelerating Spark with RDMA for Big Data Processing: Early Experiences.
Proceedings of the 22nd IEEE Annual Symposium on High-Performance Interconnects, 2014


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