What is he best known for?
The fields of study he is best known for:
- Operating system
- Central processing unit
- Electrical engineering
Norman P. Jouppi mostly deals with Parallel computing, Cache, Embedded system, Multi-core processor and Static random-access memory.
His Parallel computing research focuses on Cache coloring, CPU cache, Pipeline, Instruction set and Memory architecture.
His Embedded system study combines topics from a wide range of disciplines, such as Non-volatile memory, Computer hardware, Memory controller, Chip and Fault tolerance.
In his work, Multiprocessing, Random access memory and Tag RAM is strongly intertwined with Computer architecture, which is a subfield of Multi-core processor.
As a part of the same scientific study, he usually deals with the Static random-access memory, concentrating on Dram and frequently concerns with Universal memory and Memory hierarchy.
His studies in Page cache integrate themes in fields like Snoopy cache and MESI protocol.
His most cited work include:
- In-Datacenter Performance Analysis of a Tensor Processing Unit (2070 citations)
- McPAT: an integrated power, area, and timing modeling framework for multicore and manycore architectures (1937 citations)
- Improving direct-mapped cache performance by the addition of a small fully-associative cache and prefetch buffers (1446 citations)
What are the main themes of his work throughout his whole career to date?
Norman P. Jouppi spends much of his time researching Computer hardware, Parallel computing, Embedded system, Cache and Artificial intelligence.
His Parallel computing research is multidisciplinary, incorporating elements of Thread and Instructions per cycle.
His Embedded system research is multidisciplinary, relying on both Dram, Multi-core processor and Chip.
His research in Multi-core processor intersects with topics in Multiprocessing and Computer architecture.
All of his Cache and Cache pollution, Cache algorithms and CPU cache investigations are sub-components of the entire Cache study.
His Artificial intelligence research focuses on Computer vision and how it relates to Computer graphics.
He most often published in these fields:
- Computer hardware (23.67%)
- Parallel computing (22.04%)
- Embedded system (20.82%)
What were the highlights of his more recent work (between 2012-2021)?
- Computer hardware (23.67%)
- Parallel computing (22.04%)
- Semiconductor memory (8.98%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Computer hardware, Parallel computing, Semiconductor memory, Interleaved memory and Cache.
The concepts of his Computer hardware study are interwoven with issues in Computation and State.
As a member of one scientific family, Norman P. Jouppi mostly works in the field of Parallel computing, focusing on Central processing unit and, on occasion, Multithreading and Execution model.
His Semiconductor memory study integrates concerns from other disciplines, such as Computer architecture and Design space exploration.
His work deals with themes such as Registered memory and Embedded system, which intersect with Interleaved memory.
His Cache pollution and Cache coloring investigations are all subjects of Cache research.
Between 2012 and 2021, his most popular works were:
- In-Datacenter Performance Analysis of a Tensor Processing Unit (2070 citations)
- Kiln: closing the performance gap between systems with and without persistence support (190 citations)
- The McPAT Framework for Multicore and Manycore Architectures: Simultaneously Modeling Power, Area, and Timing (144 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Central processing unit
- Electrical engineering
His primary areas of study are Artificial neural network, Parallel computing, Computer hardware, Throughput and Embedded system.
His Parallel computing study frequently draws connections between adjacent fields such as Deep neural networks.
His work on Semiconductor memory and Dynamic random-access memory as part of general Computer hardware study is frequently linked to Phase-change memory and Numerical linear algebra, bridging the gap between disciplines.
His Embedded system study combines topics from a wide range of disciplines, such as NAND gate, Logic synthesis and Interleaved memory.
His study looks at the relationship between Central processing unit and fields such as Multithreading, as well as how they intersect with chemical problems.
His Computer architecture research is multidisciplinary, incorporating perspectives in Multi-core processor, Design space exploration and Cache.
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