What is she best known for?
The fields of study she is best known for:
- Operating system
- Central processing unit
- Programming language
Her primary areas of study are Artificial intelligence, Parallel computing, Computer hardware, Uniform memory access and Machine learning.
Her Phrase study in the realm of Artificial intelligence interacts with subjects such as Context, Cognitive science, Memory performance and Space exploration.
Her work on Memory bandwidth as part of general Parallel computing research is frequently linked to Memory wall, thereby connecting diverse disciplines of science.
Sally A. McKee works in the field of Uniform memory access, namely Non-uniform memory access.
Sally A. McKee has researched Machine learning in several fields, including Performance prediction and Supercomputer.
The Hybrid Memory Cube research she does as part of her general Dram study is frequently linked to other disciplines of science, such as Stooge sort, Bucket sort and Integer sorting, therefore creating a link between diverse domains of science.
Her most cited work include:
- Hitting the memory wall: implications of the obvious (1313 citations)
- Efficiently exploring architectural design spaces via predictive modeling (299 citations)
- Real time power estimation and thread scheduling via performance counters (262 citations)
What are the main themes of her work throughout her whole career to date?
Her scientific interests lie mostly in Parallel computing, Embedded system, Uniform memory access, Cache and Interleaved memory.
In Parallel computing, she works on issues like Compiler, which are connected to Very long instruction word.
The study incorporates disciplines such as Dynamic demand, Computer architecture, Memory hierarchy, Software and Multi-core processor in addition to Embedded system.
Sally A. McKee interconnects Memory map and Distributed memory in the investigation of issues within Uniform memory access.
Her work deals with themes such as Registered memory, Memory controller and Locality of reference, which intersect with Interleaved memory.
Her research in Memory controller intersects with topics in Dram, Memory architecture and Memory bandwidth.
She most often published in these fields:
- Parallel computing (30.25%)
- Embedded system (21.60%)
- Uniform memory access (16.67%)
What were the highlights of her more recent work (between 2013-2019)?
- Embedded system (21.60%)
- Software (12.96%)
- Operating system (9.88%)
In recent papers she was focusing on the following fields of study:
The scientist’s investigation covers issues in Embedded system, Software, Operating system, Benchmark and Dram.
Her Embedded system research includes elements of Interleaved memory, Semiconductor memory, Memory hierarchy and PCI Express.
Her research in the fields of Universal memory and Memory rank overlaps with other disciplines such as Memory wall.
Her Software research includes themes of Data center, Virtualization, Scalability and Server.
Her Benchmark study is concerned with the larger field of Parallel computing.
Her study ties her expertise on Dynamic demand together with the subject of Parallel computing.
Between 2013 and 2019, her most popular works were:
- Characterizing and subsetting big data workloads (48 citations)
- Understanding the Behavior of In-Memory Computing Workloads (44 citations)
- Exploiting Program Semantics to Place Data in Hybrid Memory (35 citations)
In her most recent research, the most cited papers focused on:
- Operating system
- Central processing unit
- Programming language
Her primary scientific interests are in Software, Embedded system, Operating system, Benchmark and Dram.
Her Software study combines topics in areas such as Memory refresh, Graph, Computer hardware, Reduction and Data analysis.
The Embedded system study combines topics in areas such as Universal memory, Interleaved memory and Static random-access memory.
Her studies in Operating system integrate themes in fields like Transactional memory, Transactional Synchronization Extensions, Software transactional memory and Programming style.
Sally A. McKee has included themes like Cluster analysis, Field and Data science in her Benchmark study.
Her Dram research is multidisciplinary, incorporating perspectives in Data validation, Efficient energy use and Memory controller.
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