What is he best known for?
The fields of study he is best known for:
- Operating system
- Programming language
- Central processing unit
Kunle Olukotun focuses on Parallel computing, Software, Operating system, Multiprocessing and Transactional memory.
His Parallel computing research is multidisciplinary, incorporating perspectives in Domain-specific language, Compiler, Speculative multithreading and Programmer.
His Operating system study integrates concerns from other disciplines, such as Instruction set and Database.
His study in Multiprocessing is interdisciplinary in nature, drawing from both Virtual machine, Microarchitecture, Java, Parallelism and Synchronization.
His study looks at the relationship between Transactional memory and fields such as Atomicity, as well as how they intersect with chemical problems.
He interconnects Multi-core processor and Cache in the investigation of issues within Thread.
His most cited work include:
- Map-Reduce for Machine Learning on Multicore (1141 citations)
- Niagara: a 32-way multithreaded Sparc processor (924 citations)
- STAMP: Stanford Transactional Applications for Multi-Processing (763 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Parallel computing, Computer architecture, Software, Compiler and Transactional memory.
His study looks at the intersection of Parallel computing and topics like Programming paradigm with Domain-specific language.
His Computer architecture study deals with Multi-core processor intersecting with Cache and Thread.
As a part of the same scientific study, he usually deals with the Cache, concentrating on Multiprocessing and frequently concerns with Speculative multithreading and Parallelism.
His work carried out in the field of Transactional memory brings together such families of science as Distributed computing, Atomicity, Transaction processing and Operating system.
His research integrates issues of Machine learning and Artificial intelligence in his study of Speedup.
He most often published in these fields:
- Parallel computing (36.95%)
- Computer architecture (18.72%)
- Software (16.75%)
What were the highlights of his more recent work (between 2017-2021)?
- Field-programmable gate array (10.84%)
- Artificial intelligence (6.90%)
- Speedup (9.36%)
In recent papers he was focusing on the following fields of study:
Kunle Olukotun mainly focuses on Field-programmable gate array, Artificial intelligence, Speedup, Machine learning and Software.
The concepts of his Field-programmable gate array study are interwoven with issues in Symmetric multiprocessor system, Distributed computing, Data modeling, Computer architecture and Graph.
His work on Deep learning as part of general Artificial intelligence study is frequently linked to Noise, bridging the gap between disciplines.
His Speedup study deals with the bigger picture of Parallel computing.
His work in Parallel computing addresses issues such as Stratix, which are connected to fields such as Abstraction layer.
His Software research includes themes of Systems design, Pareto principle, Design space exploration and Computer engineering.
Between 2017 and 2021, his most popular works were:
- High-Accuracy Low-Precision Training (61 citations)
- Spatial: a language and compiler for application accelerators (60 citations)
- Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark (30 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Programming language
- Central processing unit
The scientist’s investigation covers issues in Artificial intelligence, Software, Machine learning, Deep learning and Computation.
In general Artificial intelligence study, his work on Range often relates to the realm of Frontier, thereby connecting several areas of interest.
Kunle Olukotun brings together Software and Software framework to produce work in his papers.
The study incorporates disciplines such as Semantics and Benchmark in addition to Machine learning.
He works mostly in the field of Python, limiting it down to topics relating to Scala and, in certain cases, File format, Computer architecture, Compiler, High-level synthesis and Programmer, as a part of the same area of interest.
He has researched Computer architecture in several fields, including Field-programmable gate array and Speedup.
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