What is he best known for?
The fields of study he is best known for:
- Operating system
- Central processing unit
- Programming language
His primary scientific interests are in Operating system, Scalability, Parallel computing, Transactional memory and Server.
The Operating system study combines topics in areas such as Instruction set and Runtime system.
His Scalability research includes themes of Dram, Computer architecture, Static random-access memory, Analytics and Multi-core processor.
His study brings together the fields of Multithreading and Parallel computing.
A large part of his Transactional memory studies is devoted to Software transactional memory.
He has researched Server in several fields, including Latency, Distributed computing, Workload, Quality of service and Cloud computing.
His most cited work include:
- Evaluating MapReduce for Multi-core and Multiprocessor Systems (891 citations)
- STAMP: Stanford Transactional Applications for Multi-Processing (763 citations)
- Transactional Memory Coherence and Consistency (663 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Distributed computing, Parallel computing, Operating system, Embedded system and Transactional memory.
His Distributed computing research is multidisciplinary, relying on both Workload, Cost efficiency, Scheduling, Cloud computing and Server.
His work focuses on many connections between Server and other disciplines, such as Scalability, that overlap with his field of interest in Synchronization.
His Parallel computing study incorporates themes from Multithreading and Thread.
The study incorporates disciplines such as Dram, Multi-core processor, Computer architecture and Efficient energy use in addition to Embedded system.
His studies examine the connections between Transactional memory and genetics, as well as such issues in Software, with regards to Programming paradigm and Data structure.
He most often published in these fields:
- Distributed computing (24.07%)
- Parallel computing (21.30%)
- Operating system (20.37%)
What were the highlights of his more recent work (between 2015-2021)?
- Distributed computing (24.07%)
- Cloud computing (14.81%)
- Scheduling (12.96%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Distributed computing, Cloud computing, Scheduling, Software and Latency.
His biological study spans a wide range of topics, including Workload, Quality of service, Inference and Cost efficiency.
Cloud computing is a subfield of Operating system that Christos Kozyrakis explores.
His Scheduling research is multidisciplinary, incorporating perspectives in Scalability, Compiler, Dataflow and Efficient energy use.
As part of one scientific family, Christos Kozyrakis deals mainly with the area of Software, narrowing it down to issues related to the Programming paradigm, and often Speedup, High-level synthesis, Scala and Programmer.
His work is dedicated to discovering how Latency, Embedded system are connected with Latency and IOPS and other disciplines.
Between 2015 and 2021, his most popular works were:
- TETRIS: Scalable and Efficient Neural Network Acceleration with 3D Memory (227 citations)
- HRL: Efficient and flexible reconfigurable logic for near-data processing (95 citations)
- Plasticine: A Reconfigurable Architecture For Parallel Paterns (91 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Central processing unit
- Programming language
The scientist’s investigation covers issues in Parallel computing, Software, Distributed computing, Field-programmable gate array and Efficient energy use.
His studies in Parallel computing integrate themes in fields like Artificial neural network, Queueing theory and Dram.
His Distributed computing study integrates concerns from other disciplines, such as Quality of service, Ephemeral key, Analytics and Cost efficiency.
His Field-programmable gate array research incorporates themes from Routing and Computer architecture.
His Efficient energy use study frequently involves adjacent topics like Scheduling.
His Cloud computing research is within the category of Operating system.
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