What is he best known for?
The fields of study he is best known for:
- Operating system
- Artificial intelligence
- Programming language
His primary areas of investigation include Field-programmable gate array, Embedded system, Parallel computing, Reconfigurable computing and Computer hardware.
Wayne Luk has included themes like Logic synthesis, Software, Speedup and Computer architecture in his Field-programmable gate array study.
His Embedded system research is multidisciplinary, incorporating elements of Energy consumption, Compiler and Control reconfiguration.
His Parallel computing study combines topics from a wide range of disciplines, such as Floating point, Algorithm design, Spiking neural network and Graphics.
His Reconfigurable computing research includes themes of Coprocessor, Computer engineering, Software engineering and Programming paradigm.
The various areas that Wayne Luk examines in his Computer hardware study include Decoding methods, Low-density parity-check code, Unit in the last place and Gaussian noise.
His most cited work include:
- Reconfigurable computing: architectures and design methods (318 citations)
- Accuracy-Guaranteed Bit-Width Optimization (188 citations)
- Pipeline vectorization (158 citations)
What are the main themes of his work throughout his whole career to date?
Wayne Luk mainly focuses on Field-programmable gate array, Parallel computing, Embedded system, Computer architecture and Reconfigurable computing.
His Field-programmable gate array study deals with Computer engineering intersecting with Convolutional neural network.
His studies deal with areas such as Floating point and Computation as well as Parallel computing.
His research in Embedded system intersects with topics in Compiler and Benchmark.
His Computer architecture study incorporates themes from Hardware architecture and Design space exploration.
Wayne Luk is involved in the study of Software that focuses on Hardware acceleration in particular.
He most often published in these fields:
- Field-programmable gate array (55.83%)
- Parallel computing (26.91%)
- Embedded system (23.74%)
What were the highlights of his more recent work (between 2016-2021)?
- Field-programmable gate array (55.83%)
- Convolutional neural network (4.46%)
- Computer engineering (8.63%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Field-programmable gate array, Convolutional neural network, Computer engineering, Artificial intelligence and Speedup.
Wayne Luk is studying Reconfigurable computing, which is a component of Field-programmable gate array.
His Convolutional neural network study combines topics in areas such as Inference, Quantization, Support vector machine, Hardware acceleration and Convolution.
Wayne Luk interconnects Process, Computation, Efficient energy use and Performance prediction in the investigation of issues within Computer engineering.
His Speedup research includes elements of Algorithm, Algorithm design, Stream processing and Porting.
His research investigates the connection between Computer hardware and topics such as Overhead that intersect with problems in Embedded system.
Between 2016 and 2021, his most popular works were:
- Deep Neural Network Approximation for Custom Hardware: Where We've Been, Where We're Going (58 citations)
- Optimizing CNN-Based Object Detection Algorithms on Embedded FPGA Platforms (36 citations)
- Leveraging FPGAs for Accelerating Short Read Alignment (32 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Artificial intelligence
- Programming language
Wayne Luk mainly investigates Field-programmable gate array, Convolutional neural network, Computer engineering, Parallel computing and Artificial intelligence.
He has researched Field-programmable gate array in several fields, including Artificial neural network, Computer architecture and Hardware architecture.
His study on Convolutional neural network also encompasses disciplines like
- Frame rate which is related to area like Pruning and Block,
- Quantization which is related to area like Computer hardware, JPEG, Virtex, Data transmission and Cloud computing,
- Object detection, which have a strong connection to Software implementation, Algorithm, Workstation and Network architecture,
- Computation which connect with Robotics, Jacobian matrix and determinant, Robot kinematics and Robot,
- Feature extraction which is related to area like Design space exploration, Computational science, Computational resource and Layer.
Wayne Luk has included themes like Software performance testing, Kernel and Speedup in his Computer engineering study.
His work in the fields of Parallel computing, such as Dataflow, intersects with other areas such as Bitonic sorter.
His research integrates issues of Machine learning and Bottleneck in his study of Artificial intelligence.
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