What is he best known for?
The fields of study he is best known for:
- Operating system
- Computer network
- Central processing unit
The scientist’s investigation covers issues in InfiniBand, Operating system, Message passing, Parallel computing and Scalability.
The concepts of his InfiniBand study are interwoven with issues in Remote direct memory access, Supercomputer, Computer cluster, Distributed computing and Benchmark.
His Supercomputer research integrates issues from Algorithm design and Data transmission.
His Message passing research includes themes of Computer architecture, Polling, Computer network and Deterministic routing.
The Parallel computing study combines topics in areas such as Node and Parallel programming model.
Dhabaleswar K. Panda has researched Scalability in several fields, including Cache, Datagram, Message Passing Interface, Interconnection and Network interface.
His most cited work include:
- High performance RDMA-based MPI implementation over InfiniBand (337 citations)
- A case for high performance computing with virtual machines (301 citations)
- High performance VMM-bypass I/O in virtual machines (288 citations)
What are the main themes of his work throughout his whole career to date?
Dhabaleswar K. Panda mainly investigates InfiniBand, Parallel computing, Distributed computing, Scalability and Operating system.
His InfiniBand research incorporates elements of Remote direct memory access, Supercomputer, Message Passing Interface, Message passing and Computer architecture.
His study in Remote direct memory access is interdisciplinary in nature, drawing from both Software portability, Lustre and Big data.
His work carried out in the field of Parallel computing brings together such families of science as Partitioned global address space and Artificial intelligence.
His studies deal with areas such as Network topology, Computer network and Overhead as well as Distributed computing.
He has included themes like Latency, Multi-core processor, Embedded system, Interconnection and Network interface in his Scalability study.
He most often published in these fields:
- InfiniBand (45.02%)
- Parallel computing (32.84%)
- Distributed computing (31.37%)
What were the highlights of his more recent work (between 2015-2021)?
- Parallel computing (32.84%)
- InfiniBand (45.02%)
- Scalability (28.23%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Parallel computing, InfiniBand, Scalability, Remote direct memory access and Operating system.
The various areas that Dhabaleswar K. Panda examines in his Parallel computing study include Deep learning, Artificial intelligence and Computation.
His InfiniBand study combines topics from a wide range of disciplines, such as Computer architecture, Computer hardware, Shared memory, Message Passing Interface and Software.
His studies in Shared memory integrate themes in fields like Bottleneck, Overhead and Partitioned global address space.
His work in Scalability addresses subjects such as Distributed computing, which are connected to disciplines such as Communications protocol.
His Remote direct memory access research is multidisciplinary, relying on both Distributed database, Distributed data store, Associative array, Benchmark and Big data.
Between 2015 and 2021, his most popular works were:
- S-Caffe: Co-designing MPI Runtimes and Caffe for Scalable Deep Learning on Modern GPU Clusters (99 citations)
- High Performance Design for HDFS with Byte-Addressability of NVM and RDMA (35 citations)
- Stampede 2: The Evolution of an XSEDE Supercomputer (31 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- Central processing unit
Dhabaleswar K. Panda focuses on Parallel computing, Operating system, InfiniBand, Scalability and Remote direct memory access.
His research integrates issues of Deep learning, Artificial intelligence and Computation in his study of Parallel computing.
His research in InfiniBand intersects with topics in Virtualization, Cloud computing and Distributed computing.
His work on Message Passing Interface as part of his general Distributed computing study is frequently connected to Interface, thereby bridging the divide between different branches of science.
His Scalability research is multidisciplinary, relying on both Xeon, Reduction and Distributed Computing Environment.
His Remote direct memory access study combines topics from a wide range of disciplines, such as Implementation, Server and Big data.
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