What is he best known for?
The fields of study he is best known for:
- Operating system
- Central processing unit
- Artificial intelligence
His main research concerns Embedded system, Parallel computing, Computer architecture, Memory management and Cache.
His Embedded system research includes elements of Non-uniform memory access, Computer hardware and Distributed memory.
His Parallel computing research incorporates themes from Schedule, Bottleneck and Compiler.
In Computer architecture, he works on issues like Architecture description language, which are connected to Very long instruction word.
The concepts of his Cache study are interwoven with issues in Energy consumption and Task.
His Interleaved memory research is multidisciplinary, incorporating elements of Registered memory and Memory map.
His most cited work include:
- High ― Level Synthesis: Introduction to Chip and System Design (924 citations)
- High — Level Synthesis (636 citations)
- EXPRESSION: a language for architecture exploration through compiler/simulator retargetability (384 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Embedded system, Computer architecture, Parallel computing, High-level synthesis and System on a chip.
The Embedded system study combines topics in areas such as Cache, Energy consumption, Memory management, Software and Cache-only memory architecture.
The various areas that Nikil Dutt examines in his Computer architecture study include Compiler, Design space exploration and Architecture description language.
His research on Parallel computing often connects related topics like Scheduling.
His System on a chip research integrates issues from Multiprocessing and Electronic engineering.
Nikil Dutt has researched Interleaved memory in several fields, including Registered memory and Memory map.
He most often published in these fields:
- Embedded system (35.92%)
- Computer architecture (18.97%)
- Parallel computing (18.82%)
What were the highlights of his more recent work (between 2015-2021)?
- Embedded system (35.92%)
- Efficient energy use (5.89%)
- Distributed computing (7.61%)
In recent papers he was focusing on the following fields of study:
Nikil Dutt mainly focuses on Embedded system, Efficient energy use, Distributed computing, Resource management and Artificial intelligence.
His study in Embedded system is interdisciplinary in nature, drawing from both Interleaved memory, Flat memory model, Memory management and Software.
His biological study spans a wide range of topics, including Uniform memory access and Shared memory.
Memory management is often connected to Computer architecture in his work.
His studies deal with areas such as Energy consumption, Energy, Real-time computing and Graphics as well as Efficient energy use.
His Distributed computing research is multidisciplinary, incorporating perspectives in Workload, Power management, Dynamic priority scheduling, Exploit and Multi-core processor.
Between 2015 and 2021, his most popular works were:
- HiCH: Hierarchical Fog-Assisted Computing Architecture for Healthcare IoT (66 citations)
- Toward Smart Embedded Systems: A Self-aware System-on-Chip (SoC) Perspective (55 citations)
- SPARTA: runtime task allocation for energy efficient heterogeneous many-cores (50 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Artificial intelligence
- Central processing unit
His primary areas of study are Embedded system, Efficient energy use, Distributed computing, Artificial intelligence and Software.
He studies System on a chip, a branch of Embedded system.
Nikil Dutt combines subjects such as Exploit and Graphics with his study of Efficient energy use.
His studies in Distributed computing integrate themes in fields like Multi-core processor, Dynamic priority scheduling, Neuron and Reinforcement learning.
His research in the fields of Neuromorphic engineering and Recurrent neural network overlaps with other disciplines such as Smooth pursuit and Retinal.
His Software research is multidisciplinary, relying on both Model-based design, Software engineering and Function.
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