What is he best known for?
The fields of study he is best known for:
- Operating system
- Central processing unit
- Programming language
The scientist’s investigation covers issues in Dram, Embedded system, Computer hardware, Parallel computing and Scheduling.
The Dram study combines topics in areas such as Universal memory, Memory rank, Random access memory and Latency.
His Embedded system research includes themes of Scalability, Interleaved memory and Profiling.
His Flash memory study, which is part of a larger body of work in Computer hardware, is frequently linked to Nand flash memory, bridging the gap between disciplines.
His Parallel computing research is multidisciplinary, incorporating perspectives in Sense amplifier and Bitwise operation.
His Scheduling research incorporates themes from Microcontroller, Thread, Instruction prefetch and CUDA.
His most cited work include:
- Architecting phase change memory as a scalable dram alternative (1262 citations)
- Personalized copy number and segmental duplication maps using next-generation sequencing (665 citations)
- Flipping bits in memory without accessing them: an experimental study of DRAM disturbance errors (533 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Dram, Embedded system, Parallel computing, Cache and Distributed computing.
His Dram study introduces a deeper knowledge of Computer hardware.
His work on Flash memory as part of general Computer hardware study is frequently linked to Flash, therefore connecting diverse disciplines of science.
Onur Mutlu has included themes like Exploit, Software, Memory controller and Chip in his Embedded system study.
His study in Parallel computing is interdisciplinary in nature, drawing from both Interleaved memory, Scheduling and Thread.
His Distributed computing research incorporates themes from Scalability, Shared memory, Computer network, Multi-core processor and Programming paradigm.
He most often published in these fields:
- Dram (30.39%)
- Embedded system (26.34%)
- Parallel computing (21.73%)
What were the highlights of his more recent work (between 2019-2021)?
- Embedded system (26.34%)
- Dram (30.39%)
- Energy consumption (9.94%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Embedded system, Dram, Energy consumption, Efficient energy use and Scalability.
His Embedded system research includes elements of Spec#, Latency, Chip, Memory bank and Key.
Dram is a subfield of Computer hardware that he explores.
His work in Computer hardware tackles topics such as Quantization which are related to areas like Field-programmable gate array.
His study focuses on the intersection of Energy consumption and fields such as Bottleneck with connections in the field of Memory bandwidth, Computation and Parallel computing.
His Scalability research is multidisciplinary, relying on both Construct, Distributed computing, Algorithm and Source code.
Between 2019 and 2021, his most popular works were:
- RowHammer: A Retrospective (47 citations)
- TRRespass: Exploiting the Many Sides of Target Row Refresh (29 citations)
- Improving phase change memory performance with data content aware access (24 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Central processing unit
- Programming language
His primary areas of study are Dram, Embedded system, Energy consumption, Scalability and Efficient energy use.
Onur Mutlu integrates Dram and Bit error rate in his research.
His biological study spans a wide range of topics, including Overhead, Data access, Memory bank, Data retention and Scheduling.
His work deals with themes such as Bottleneck and Latency, which intersect with Energy consumption.
He works mostly in the field of Scalability, limiting it down to topics relating to Algorithm and, in certain cases, Identification.
Cache is the subject of his research, which falls under Parallel computing.
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