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 Parallel computing, Microprocessor, Computer hardware, Artificial neural network and Accumulator.
His Parallel computing research incorporates themes from Microcode and x86.
He has researched Microprocessor in several fields, including Control logic, Stack, Set, Opcode and Instruction register.
His study explores the link between Opcode and topics such as Instruction set that cross with problems in Execution unit.
The concepts of his Computer hardware study are interwoven with issues in Cache pollution, Cache algorithms, Instruction prefetch and Sequence.
His Accumulator study integrates concerns from other disciplines, such as Discrete mathematics, Operand, Arithmetic and Multiplexing.
His most cited work include:
- Static branch prediction mechanism for conditional branch instructions (109 citations)
- Apparatus and method for selectively overriding return stack prediction in response to detection of non-standard return sequence (66 citations)
- Microprocessor and method for performing selective prefetch based on bus activity level (63 citations)
What are the main themes of his work throughout his whole career to date?
G. Glenn Henry mainly investigates Microprocessor, Computer hardware, Operating system, Cache and Parallel computing.
His Microprocessor research is multidisciplinary, relying on both Microcode, Instruction set, Encryption and Opcode.
His biological study spans a wide range of topics, including Execution unit and Instruction register.
A large part of his Computer hardware studies is devoted to Operand.
His work deals with themes such as Artificial neural network and Accumulator, which intersect with Operand.
His Mode, Computer program and Pipeline study in the realm of Operating system interacts with subjects such as Product.
He most often published in these fields:
- Microprocessor (51.20%)
- Computer hardware (49.40%)
- Operating system (16.47%)
What were the highlights of his more recent work (between 2015-2020)?
- Computer hardware (49.40%)
- Artificial neural network (8.08%)
- Accumulator (5.99%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Computer hardware, Artificial neural network, Accumulator, Arithmetic and Operating system.
G. Glenn Henry works in the field of Computer hardware, focusing on Microprocessor in particular.
G. Glenn Henry has included themes like Synchronizing, Computer program and Encryption in his Microprocessor study.
His Artificial neural network research includes elements of Multiplexing, Word, Buffer and Row.
His research integrates issues of Operand, Multiplexer, Activation function and Algorithm in his study of Accumulator.
His research in Operating system intersects with topics in Control logic and Instruction set.
Between 2015 and 2020, his most popular works were:
- Processor with hybrid coprocessor/execution unit neural network unit (38 citations)
- Apparatus employing user-specified binary point fixed point arithmetic (38 citations)
- Processor with variable rate execution unit (38 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Central processing unit
- Programming language
G. Glenn Henry focuses on Artificial neural network, Accumulator, Arithmetic, Neural processing and Operand.
G. Glenn Henry interconnects Computer hardware, Buffer and Row in the investigation of issues within Artificial neural network.
His Computer hardware research is multidisciplinary, incorporating elements of CPU cache and Cache.
His Accumulator research includes themes of Point, Value, Multiplexer, Algorithm and Multiplexing.
His work carried out in the field of Arithmetic brings together such families of science as Execution unit, Word, Series and Parallel computing.
G. Glenn Henry focuses mostly in the field of Parallel computing, narrowing it down to topics relating to Variable and, in certain cases, Control unit and Instruction set.
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