What is he best known for?
The fields of study he is best known for:
- Operating system
- Programming language
- Software
Parallel computing, Profiling, Operating system, Software and Programming language are his primary areas of study.
His Parallel computing research focuses on MESIF protocol, CPU cache, Cache coloring, Cache pollution and Cache.
His work deals with themes such as Program analysis, Compiler, Performance tuning, Tracing and Basic block, which intersect with Profiling.
In Operating system, he works on issues like Transactional memory, which are connected to Atomicity.
The various areas that James R. Larus examines in his Software study include Computer security, Computer architecture, Software deployment and Web search engine.
His research in Shared memory intersects with topics in Data diffusion machine, Distributed computing and Memory management.
His most cited work include:
- A reconfigurable fabric for accelerating large-scale datacenter services (639 citations)
- Mining specifications (605 citations)
- Efficient path profiling (556 citations)
What are the main themes of his work throughout his whole career to date?
James R. Larus focuses on Parallel computing, Programming language, Operating system, Software and Shared memory.
His Parallel computing research is multidisciplinary, incorporating elements of Compiler, Data structure and Computation.
While the research belongs to areas of Programming language, James R. Larus spends his time largely on the problem of Multiprocessing, intersecting his research to questions surrounding Workstation.
His Software research incorporates themes from Interface, Cloud computing, Software engineering and Embedded system.
The concepts of his Shared memory study are interwoven with issues in Message passing, Distributed computing and Uniform memory access, Distributed shared memory.
As part of one scientific family, James R. Larus deals mainly with the area of Distributed computing, narrowing it down to issues related to the Cache coherence, and often Protocol.
He most often published in these fields:
- Parallel computing (21.34%)
- Programming language (18.58%)
- Operating system (14.23%)
What were the highlights of his more recent work (between 2012-2021)?
- Embedded system (7.11%)
- Non-volatile memory (2.37%)
- Algorithm (5.14%)
In recent papers he was focusing on the following fields of study:
James R. Larus mainly investigates Embedded system, Non-volatile memory, Algorithm, Parallel computing and Data structure.
His Embedded system research is multidisciplinary, incorporating perspectives in Dram, Software, Server and Transient.
The Software study which covers PCI Express that intersects with Scheduling, Concurrency, Coprocessor and Design space exploration.
As a part of the same scientific family, James R. Larus mostly works in the field of Algorithm, focusing on Speedup and, on occasion, Scalability and Parallel algorithm.
His research integrates issues of Metadata and Presentation in his study of Parallel computing.
James R. Larus has researched Data structure in several fields, including CPU cache and State.
Between 2012 and 2021, his most popular works were:
- A reconfigurable fabric for accelerating large-scale datacenter services (639 citations)
- Decentralized Privacy-Preserving Proximity Tracing (80 citations)
- SIMD parallelization of applications that traverse irregular data structures (45 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Programming language
- Software
James R. Larus mainly focuses on Embedded system, Server, Software, Computer security and Non-volatile memory.
The study incorporates disciplines such as Dram, Market fragmentation, Overhead and Memory management in addition to Embedded system.
The Server study combines topics in areas such as Reconfigurable computing and Web search engine.
In general Software study, his work on Hardware acceleration often relates to the realm of Plane, thereby connecting several areas of interest.
The various areas that James R. Larus examines in his Computer security study include Tracing and Upload.
His Non-volatile memory study combines topics from a wide range of disciplines, such as CPU cache, State and Transient.
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