What is he best known for?
The fields of study he is best known for:
- Programming language
- Operating system
- Central processing unit
John Mellor-Crummey mainly investigates Parallel computing, Distributed computing, Compiler, Software and Debugging.
John Mellor-Crummey is studying Shared memory, which is a component of Parallel computing.
His Distributed computing research integrates issues from Workflow technology, Windows Workflow Foundation, Workflow engine, Workflow application and Two-level scheduling.
His Compiler study integrates concerns from other disciplines, such as Node, Parallel processing, Fortran and Source code.
His Application software study, which is part of a larger body of work in Software, is frequently linked to Grid computing and Grid application, bridging the gap between disciplines.
His Debugging study incorporates themes from Program analysis and Profiling.
His most cited work include:
- Algorithms for scalable synchronization on shared-memory multiprocessors (1128 citations)
- Terascale direct numerical simulations of turbulent combustion using S3D (420 citations)
- HPCTOOLKIT: tools for performance analysis of optimized parallel programs (399 citations)
What are the main themes of his work throughout his whole career to date?
John Mellor-Crummey mostly deals with Parallel computing, Compiler, Scalability, Distributed computing and Fortran.
His Parallel computing study combines topics from a wide range of disciplines, such as High Performance Fortran, Computation and Programming paradigm.
His study looks at the intersection of Compiler and topics like Source code with Instrumentation.
His Scalability research includes elements of Node, SPMD, Profiling and Asynchronous communication.
His Distributed computing research includes themes of Synchronization and Latency.
His biological study deals with issues like Message passing, which deal with fields such as Itanium.
He most often published in these fields:
- Parallel computing (50.85%)
- Compiler (32.20%)
- Scalability (20.34%)
What were the highlights of his more recent work (between 2013-2021)?
- Parallel computing (50.85%)
- Distributed computing (18.08%)
- Programming paradigm (9.60%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Parallel computing, Distributed computing, Programming paradigm, Scalability and Computation.
John Mellor-Crummey has researched Parallel computing in several fields, including Program optimization, Compiler, Data-flow analysis and Code generation.
The various areas that John Mellor-Crummey examines in his Compiler study include Bottleneck and Principal.
His study on Concurrency is often connected to SPIN model checker as part of broader study in Distributed computing.
As part of one scientific family, John Mellor-Crummey deals mainly with the area of Scalability, narrowing it down to issues related to the Process, and often Cluster, Shell, Parallelism and Message passing.
His research integrates issues of Microprocessor, Multiprocessing, Measure and Cache-only memory architecture in his study of Computation.
Between 2013 and 2021, his most popular works were:
- A tool to analyze the performance of multithreaded programs on NUMA architectures (51 citations)
- High performance locks for multi-level NUMA systems (44 citations)
- A wait-free queue as fast as fetch-and-add (31 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Programming language
- Central processing unit
John Mellor-Crummey spends much of his time researching Distributed computing, Parallel computing, Memory hierarchy, Operating system and Embedded system.
His work deals with themes such as Queue, Cache contention and Computer hardware, which intersect with Distributed computing.
The study incorporates disciplines such as Scalability and Memory management in addition to Parallel computing.
His Operating system research incorporates elements of Control flow, Call control, Call management and Computer engineering.
His Embedded system research incorporates themes from Ticket lock, Queueing theory, Computation and Memory access pattern.
His SIMD research is multidisciplinary, incorporating elements of SPMD, Dynamic data, Concurrency, Shared memory and Instruction set.
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