World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
10010
World Ranking
5866
National Ranking
2657

Overview

Leonid Oliker is affiliated with the Lawrence Berkeley National Laboratory in the United States. Their research focuses primarily on the field of Computer Science, with a particular emphasis on Computer Networks and Communications, Hardware and Architecture, and Information Systems. Their work also crosses into Molecular Biology and Food Science, reflecting a multidisciplinary approach.

Their scientific contributions cover several main topics, including Advanced Data Storage Technologies, Parallel Computing and Optimization Techniques, and Cloud Computing and Resource Management. Additionally, they have contributed to studies involving Distributed and Parallel Computing Systems, Genomics and Phylogenetic Studies, Probiotics and Fermented Foods, and Gut Microbiota and Health.

Oliker's publication record includes papers in various venues: arXiv (Cornell University), Concurrency and Computation Practice and Experience, bioRxiv (Cold Spring Harbor Laboratory), the 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), and OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).

  • Evaluating the potential of disaggregated memory systems for HPC applications, 2024, Concurrency and Computation Practice and Experience
  • GenomeFace: a deep learning-based metagenome binner trained on 43,000 microbial genomes, 2024, bioRxiv (Cold Spring Harbor Laboratory)
  • Preprocessing Pipeline Optimization for Scientific Deep Learning Workloads, 2022, 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
  • FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings (FTL) v1.0, 2024, OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)
  • Evaluating the Potential of Disaggregated Memory Systems for HPC applications, 2023, arXiv (Cornell University)

Frequent collaborators in their research include Samuel Williams, Muaaz Gul Awan, Zhe Bai, Pieter Maris, and Hai Ah Nam. These partnerships have contributed to multiple projects and publications, particularly in areas related to high-performance computing and deep learning applications.

Best Publications

  • Optimization of sparse matrix-vector multiplication on emerging multicore platforms

    Samuel Williams;Leonid Oliker;Richard Vuduc;John Shalf

  • Optimization of sparse matrix-vector multiplication on emerging multicore platforms

    Samuel Williams;Leonid Oliker;Richard Vuduc;John Shalf

  • Stencil computation optimization and auto-tuning on state-of-the-art multicore architectures

    Kaushik Datta;Mark Murphy;Vasily Volkov;Samuel Williams

  • The potential of the cell processor for scientific computing

    Samuel Williams;John Shalf;Leonid Oliker;Shoaib Kamil

  • Optimization and Performance Modeling of Stencil Computations on Modern Microprocessors

    Kaushik Datta;Shoaib Kamil;Samuel Williams;Leonid Oliker

  • A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome

    Jarrod A Chapman;Martin Mascher;Aydın Buluç;Kerrie Barry

  • An auto-tuning framework for parallel multicore stencil computations

    Shoaib Kamil;Cy Chan;Leonid Oliker;John Shalf

  • Implicit and explicit optimizations for stencil computations

    Shoaib Kamil;Kaushik Datta;Samuel Williams;Leonid Oliker

  • PLUM: parallel load balancing for adaptive unstructured meshes

    Leonid Oliker;Rupak Biswas

  • Reduced-Bandwidth Multithreaded Algorithms for Sparse Matrix-Vector Multiplication

    Aydin Buluç;Samuel Williams;Leonid Oliker;James Demmel

  • Job Superscheduler Architecture and Performance in Computational Grid Environments

    Hongzhang Shan;Leonid Oliker;Rupak Biswas

  • Scientific Computing Kernels on the Cell Processor

    Samuel W. Williams;John Shalf;Leonid Oliker;Shoaib Kamil

  • Lattice Boltzmann simulation optimization on leading multicore platforms

    S. Williams;J. Carter;L. Oliker;J. Shalf

  • Impact of modern memory subsystems on cache optimizations for stencil computations

    Shoaib Kamil;Parry Husbands;Leonid Oliker;John Shalf

  • Roofline Model Toolkit: A Practical Tool for Architectural and Program Analysis

    Yu Jung Lo;Samuel Williams;Brian Van Straalen;Terry J. Ligocki

  • Scientific Computations on Modern Parallel Vector Systems

    Leonid Oliker;Andrew Canning;Jonathan Carter;John Shalf

  • Analyzing Ultra-Scale Application Communication Requirements for a Reconfigurable Hybrid Interconnect

    John Shalf;Shoaib Kamil;Leonid Oliker;David Skinner

  • Effects of Ordering Strategies and Programming Paradigms on Sparse Matrix Computations

    Leonid Oliker;Xiaoye Li;Parry Husbands;Rupak Biswas

  • Parallel de bruijn graph construction and traversal for de novo genome assembly

    Evangelos Georganas;Aydin Buluc;Jarrod Chapman;Leonid Oliker

  • Investigation of leading HPC I/O performance using a scientific-application derived benchmark

    Julian Borrill;Leonid Oliker;John Shalf;Hongzhang Shan

  • Sparse Matrix-Vector Multiplication on Multicore and Accelerators

    Samuel Williams;Nathan Bell;Jee Whan Choi;Michael Garland

Frequent Co-Authors

Samuel Williams
Samuel Williams Lawrence Berkeley National Laboratory
John Shalf
John Shalf Lawrence Berkeley National Laboratory
Katherine Yelick
Katherine Yelick University of California, Berkeley
Rupak Biswas
Rupak Biswas Ames Research Center
Shoaib Kamil
Shoaib Kamil Adobe Systems (United States)
Aydin Buluc
Aydin Buluc Lawrence Berkeley National Laboratory
John R. Gilbert
John R. Gilbert University of California, Santa Barbara
Daniel S. Rokhsar
Daniel S. Rokhsar University of California, Berkeley
Richard Vuduc
Richard Vuduc Georgia Institute of Technology
Michael F. Wehner
Michael F. Wehner Lawrence Berkeley National Laboratory

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