Welcome to the Network-Based Computing (NBC) Laboratory at the Computer Science and Engineering Department!
Many state-of-the-art and exciting research projects are being carried out by various members of the group, including:
- High Performance MPI on Infiniband Cluster
- Programming model support for Co-Processor (GPU & MIC)
- High Performance Computing with Virtualization
- Scalable Filesystems and I/O
- Performance Evaluation of Cluster Networking and I/O Technologies
- Networking, Storage and Middleware Support for Cloud Computing and DataCenters
- High Performance Runtime for PGAS Models (OpenSHMEM, UPC and CAF)
- BigData (Hadoop,Spark & Memcached)
The MVAPICH2 software, based on MPI 3.1 standard, delivers the best performance, scalability and fault tolerance for high-end computing systems and servers using InfiniBand, Omni-Path, Ethernet/iWARP, and RoCE networking technologies. This software is being used by more than 2650 organizations in 83 countries worldwide to extract the potential of these emerging networking technologies for modern systems. As of September'16, more than 390,000 downloads have taken place from this project's site. This software is also being distributed by many vendors as part of their software distributions.
Multiple software libraries for Big Data processing and management, designed and developed by the group under High-Performance Big Data (HiBD) Project are available. These include: 1) RDMA-enabled Apache Hadoop Software library providing native RDMA (InfiniBand Verbs and RoCE) support for multiple components (HDFS, MapReduce and RPC) of Apache Hadoop; 2) RDMA-enabled Spark Software library providing native RDMA (InfiniBand Verbs and RoCE) support; 3) RDMA-Memcached Software library for providing native RDMA (InfiniBand Verbs and RoCE) support for Memcached used in Web 2.0 environment; and 4) OSU High-performance Big data Benchmarks (OHB). Sample performance numbers and download instructions for these packages are available from the above-mentioned website. These libraries are currently being used by more than 190 organizations worldwide (in 26 countries). More than 17,900 downloads of this software have taken place from the project website alone.
The objectives of the research group are as follows:
- Proposing new designs for high performance network-based computing systems by taking advantages of modern networking technologies and computing systems
- Developing better middleware, API, and programming environments so that modern network-based computing applications can be developed and implemented in a scalable and high performance manner
- Performing the above research in an integrated manner (by taking systems, networking, and applications into account)
- Focusing on experimental computer science research
Multiple Positions available in the group:
1) Post-Doc/Research Scientist
2) MPI Software Engineer/Programmer
The projects in the Laboratory are funded by U.S. National Science Foundation, U.S. DOE Office of Science, Ohio Board of Regents, Ohio Department of Development, Cisco Systems, Cray, Intel, Linux Networx, Mellanox, NVIDIA, QLogic, and Sun Microsystems; and equipment donations from Advanced Clustering, AMD, Appro, Chelsio, Dell, Fulcrum, Fujitsu, Intel, Mellanox, Microway, NetEffect, QLogic and Sun. Other technology partner includes: TotalView.
(NEW) The HiBD team to Provide Big Data Computing Expertise for Neuroscience in NSF BD-Spoke Project.
Upcoming Tutorials: Accelerating Big Data Processing with Hadoop, Spark and Memcached at Hot Interconnect 2016, Field Programmable Logic and Applications (FPL '16), IEEE Cluster 2016, and Supercomputing 2016. Past Tutorials presented at: ISCA 2016, CCGrid 2016, ASPLOS 2016, and HPCA 2016.
4th Annual MVAPICH User Group (MUG) Meeting took place on August 15-17, 2016 in Columbus, Ohio, USA. Click here for presentation slides and videos.
Upcoming Tutorials: MVAPICH2 optimization and tuning at XSEDE '16, MPI+PGAS at IEEE Cluster '16, IB and HSE at SC '16. Past tutorials of IB and HSE presented at ISC '16, MPI+PGAS presented at ICS '16 and PPoPP '16.
Talk on Big Data Acceleration Presented at Hadoop Summit, Dublin, Ireland.