What is he best known for?
The fields of study he is best known for:
- Operating system
- Central processing unit
- Microsoft Windows
His primary areas of investigation include Parallel computing, Software, Computer architecture, General-purpose computing on graphics processing units and Cache.
In general Parallel computing study, his work on Branch predictor, Supercomputer and Graphics processing unit often relates to the realm of Branch target predictor and Branch predication, thereby connecting several areas of interest.
His study in Software is interdisciplinary in nature, drawing from both Simics, Embedded system, Microarchitecture, Failure rate and Fault tolerance.
The Computer architecture study combines topics in areas such as Symmetric multiprocessor system, Correctness, Collaborative computing and Modular design.
His Symmetric multiprocessor system research is multidisciplinary, relying on both Profiling, Plug-in, Benchmark, Parallel algorithm and Debugging.
His biological study spans a wide range of topics, including Coprocessor, CUDA Pinned memory, Memory model, CUDA and Speedup.
His most cited work include:
- Multi2Sim: a simulation framework for CPU-GPU computing (337 citations)
- Heterogeneous Computing with OpenCL (182 citations)
- VMM-based intrusion detection system (180 citations)
What are the main themes of his work throughout his whole career to date?
David Kaeli spends much of his time researching Parallel computing, Embedded system, Computer architecture, Graphics and Scalability.
His Parallel computing study typically links adjacent topics like General-purpose computing on graphics processing units.
The concepts of his General-purpose computing on graphics processing units study are interwoven with issues in Symmetric multiprocessor system and CUDA.
His Embedded system study integrates concerns from other disciplines, such as Side channel attack and Key.
His study brings together the fields of Software and Computer architecture.
Cache is represented through his CPU cache and Cache algorithms research.
He most often published in these fields:
- Parallel computing (31.03%)
- Embedded system (14.59%)
- Computer architecture (13.00%)
What were the highlights of his more recent work (between 2015-2021)?
- Parallel computing (31.03%)
- Embedded system (14.59%)
- Graphics (9.02%)
In recent papers he was focusing on the following fields of study:
David Kaeli mainly focuses on Parallel computing, Embedded system, Graphics, Instruction set and Computer engineering.
His Parallel computing research incorporates elements of Timing attack, Side channel attack and Thread.
His Graphics research is multidisciplinary, incorporating perspectives in Computer architecture and Supercomputer.
His studies deal with areas such as General-purpose computing on graphics processing units, Hardware architecture, Kernel and Microarchitecture as well as Computer architecture.
His research in Instruction set intersects with topics in Scheduling, CUDA and Scalability.
His research investigates the connection between Reliability and topics such as Software that intersect with problems in Benchmark.
Between 2015 and 2021, his most popular works were:
- Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms (68 citations)
- Hetero-mark, a benchmark suite for CPU-GPU collaborative computing (57 citations)
- A complete key recovery timing attack on a GPU (52 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Central processing unit
- Microsoft Windows
His primary areas of investigation include Parallel computing, Graphics, Computer architecture, Embedded system and Kernel.
David Kaeli combines subjects such as Deep learning and Computer hardware with his study of Parallel computing.
His Graphics study also includes fields such as
- Reliability that connect with fields like Prism, Supercomputer and Fault tolerance,
- Computer engineering that intertwine with fields like Rendering, Byte, Concurrency and Power analysis.
His work carried out in the field of Computer architecture brings together such families of science as Symmetric multiprocessor system, General-purpose computing on graphics processing units and Benchmark.
His studies examine the connections between Embedded system and genetics, as well as such issues in Key, with regards to Operating system.
David Kaeli interconnects Scheduling and CUDA in the investigation of issues within Instruction set.
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