What is he best known for?
The fields of study he is best known for:
- Operating system
- Central processing unit
- Computer network
His primary scientific interests are in Operating system, Energy consumption, Embedded system, Efficient energy use and Throughput.
The Energy consumption study combines topics in areas such as Single-core, Integrated circuit design, Electronic engineering and Subthreshold conduction.
His Single-core course of study focuses on Chip and CPU cache and Multi-core processor.
His Integrated circuit design study combines topics in areas such as Low voltage, Energy conservation, Moore's law and Low-power electronics.
His Embedded system research is multidisciplinary, incorporating elements of Discrete event simulation, Computer architecture simulator, Simulation and Power system simulator for engineering.
His Server study combines topics from a wide range of disciplines, such as Computer architecture, Service, Deep learning, Artificial intelligence and CUDA.
His most cited work include:
- The M5 Simulator: Modeling Networked Systems (739 citations)
- Near-Threshold Computing: Reclaiming Moore's Law Through Energy Efficient Integrated Circuits (629 citations)
- A survey of multicore processors (224 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Embedded system, Parallel computing, Efficient energy use, Computer hardware and Cache.
Ronald G. Dreslinski interconnects Dram, Latency, Random access memory, Power management and Multi-core processor in the investigation of issues within Embedded system.
His Speedup and SIMD study in the realm of Parallel computing connects with subjects such as Throughput.
Ronald G. Dreslinski has included themes like Energy consumption, Voltage, Single-core, Subthreshold conduction and Electronic engineering in his Efficient energy use study.
His Energy consumption research includes themes of Controller and Energy conservation.
His studies deal with areas such as Low voltage and Electrical engineering as well as Electronic engineering.
He most often published in these fields:
- Embedded system (28.32%)
- Parallel computing (22.12%)
- Efficient energy use (20.35%)
What were the highlights of his more recent work (between 2017-2021)?
- Computer architecture (11.50%)
- Chip (6.19%)
- Parallel computing (22.12%)
In recent papers he was focusing on the following fields of study:
Ronald G. Dreslinski mainly focuses on Computer architecture, Chip, Parallel computing, RISC-V and CMOS.
His study looks at the relationship between Computer architecture and fields such as Dennard scaling, as well as how they intersect with chemical problems.
His Chip study integrates concerns from other disciplines, such as Multiplication, Distributed computing and Memory hierarchy.
Parallel computing is often connected to Bottleneck in his work.
His RISC-V research is multidisciplinary, incorporating perspectives in Manycore processor, Router, Giga-, Benchmark and Efficient energy use.
His CMOS study is associated with Electronic engineering.
Between 2017 and 2021, his most popular works were:
- OuterSPACE: An Outer Product Based Sparse Matrix Multiplication Accelerator (54 citations)
- The Celerity Open-Source 511-Core RISC-V Tiered Accelerator Fabric: Fast Architectures and Design Methodologies for Fast Chips (32 citations)
- A 1.4 GHz 695 Giga Risc-V Inst/s 496-Core Manycore Processor With Mesh On-Chip Network and an All-Digital Synthesized PLL in 16nm CMOS (9 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Central processing unit
- Computer network
Sparse matrix, RISC-V, Multiplication, Matrix multiplication and Massively parallel are his primary areas of study.
His research integrates issues of Manycore processor, Giga- and Router in his study of RISC-V.
His studies in Router integrate themes in fields like Scalability, Bandwidth and Parallel computing.
His research in Multiplication intersects with topics in Chip, Systolic array and Memory hierarchy, Cache.
His Massively parallel study incorporates themes from Computer architecture, High-level synthesis, Reduced instruction set computing, Efficient energy use and Global address space.
With his scientific publications, his incorporates both Computer hardware and Throughput.
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