What is he best known for?
The fields of study he is best known for:
- Operating system
- Computer network
- Parallel computing
Jung Ho Ahn spends much of his time researching Computer architecture, Embedded system, Dram, Cache and Multi-core processor.
The study incorporates disciplines such as Configuration management and Concurrency in addition to Computer architecture.
His Embedded system study combines topics in areas such as Photonics, Thread and Multiplexing, Chip, Electrical engineering.
His Dram research includes themes of Universal memory and Memory rank.
His Cache research is multidisciplinary, incorporating perspectives in Manycore processor and Random access memory.
His Manycore processor study also includes
- Multiprocessing and related Cluster analysis, Ethernet, Dark silicon and CMOS,
- Overhead which intersects with area such as Hybrid Memory Cube.
His most cited work include:
- McPAT: an integrated power, area, and timing modeling framework for multicore and manycore architectures (1937 citations)
- Corona: System Implications of Emerging Nanophotonic Technology (542 citations)
- Programmable stream processors (304 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Parallel computing, Dram, Embedded system, Computer hardware and Cache.
The concepts of his Dram study are interwoven with issues in Latency, Memory rank, Static random-access memory, Universal memory and CAS latency.
His research integrates issues of Data transmission, Interleaved memory, Conventional memory, Registered memory and Efficient energy use in his study of Embedded system.
He has included themes like Computer architecture and Multi-core processor in his Cache study.
Jung Ho Ahn interconnects Manycore processor and Usability in the investigation of issues within Computer architecture.
His research in Multi-core processor focuses on subjects like Multiprocessing, which are connected to Design space exploration and Overhead.
He most often published in these fields:
- Parallel computing (31.30%)
- Dram (31.30%)
- Embedded system (30.43%)
What were the highlights of his more recent work (between 2016-2021)?
- Dram (31.30%)
- Parallel computing (31.30%)
- Embedded system (30.43%)
In recent papers he was focusing on the following fields of study:
Dram, Parallel computing, Embedded system, Server and Cache are his primary areas of study.
His Dram research integrates issues from CAS latency, Efficient energy use and Data transmission.
In his study, Dram cache, Pipeline burst cache, Computer architecture and Bandwidth is strongly linked to Static random-access memory, which falls under the umbrella field of CAS latency.
His work on Memory hierarchy as part of his general Parallel computing study is frequently connected to Multiplication and Throughput, thereby bridging the divide between different branches of science.
As a part of the same scientific family, Jung Ho Ahn mostly works in the field of Embedded system, focusing on Latency and, on occasion, Random access and Response time.
His study in Workload is interdisciplinary in nature, drawing from both Isolation, Multiprocessing and Multi-core processor.
Between 2016 and 2021, his most popular works were:
- Memory Hierarchy for Web Search (32 citations)
- Defect Analysis and Cost-Effective Resilience Architecture for Future DRAM Devices (23 citations)
- Restructuring Batch Normalization to Accelerate CNN Training. (18 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Computer network
- Parallel computing
His main research concerns Dram, Row, Computer hardware, Parallel computing and Normalization.
His Dram study combines topics in areas such as Efficient energy use and Reliability.
Jung Ho Ahn has researched Reliability in several fields, including Decoding methods, Embedded system, Access time and Resilience.
His Row research overlaps with Energy, Probabilistic logic and Cache.
Many of his research projects under Parallel computing are closely connected to Smoothing with Smoothing, tying the diverse disciplines of science together.
Jung Ho Ahn has included themes like Speech recognition and Convolutional neural network in his Normalization study.
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