What is he best known for?
The fields of study he is best known for:
- Operating system
- Central processing unit
- Programming language
His scientific interests lie mostly in Embedded system, Parallel computing, Energy consumption, Cache and Compiler.
His research in Embedded system is mostly focused on Memory architecture.
In his research, Energy conservation is intimately related to Dram, which falls under the overarching field of Memory architecture.
Mahmut Kandemir has researched Parallel computing in several fields, including Scheduling, Thread and Loop nest optimization.
His Energy consumption research incorporates themes from Optimizing compiler, Process, Distributed computing and Leakage.
His Compiler research also works with subjects such as
- Computer architecture and related Chip and Set,
- Data parallelism most often made with reference to Data access.
His most cited work include:
- Leakage current: Moore's law meets static power (972 citations)
- The design and use of simplepower: a cycle-accurate energy estimation tool (438 citations)
- DRPM: dynamic speed control for power management in server class disks (386 citations)
What are the main themes of his work throughout his whole career to date?
Mahmut Kandemir mainly investigates Parallel computing, Embedded system, Compiler, Cache and Energy consumption.
His research in Parallel computing tackles topics such as Loop nest optimization which are related to areas like Loop interchange.
In his study, Distributed memory is strongly linked to Memory management, which falls under the umbrella field of Embedded system.
His work deals with themes such as Scheme, Data access, Computer architecture and Set, which intersect with Compiler.
Many of his studies on Cache apply to Distributed computing as well.
His Energy consumption study integrates concerns from other disciplines, such as Real-time computing, Efficient energy use and Integer programming.
He most often published in these fields:
- Parallel computing (42.69%)
- Embedded system (30.13%)
- Compiler (25.26%)
What were the highlights of his more recent work (between 2014-2021)?
- Parallel computing (42.69%)
- Embedded system (30.13%)
- Cache (23.72%)
In recent papers he was focusing on the following fields of study:
Mahmut Kandemir mainly focuses on Parallel computing, Embedded system, Cache, Scheduling and Software.
He has included themes like Latency, Compiler, System on a chip, Interleaved memory and General-purpose computing on graphics processing units in his Parallel computing study.
His Embedded system research is multidisciplinary, incorporating perspectives in Scalability and Multi-core processor.
His study in Cache is interdisciplinary in nature, drawing from both Multiprocessing, Overhead, Data access and Static random-access memory.
His Scheduling research includes themes of Queue, Provisioning, Distributed computing and Microservices.
His research investigates the connection with Software and areas like Idle which intersect with concerns in Memory bandwidth.
Between 2014 and 2021, his most popular works were:
- Scheduling Techniques for GPU Architectures with Processing-In-Memory Capabilities (108 citations)
- A case for core-assisted bottleneck acceleration in GPUs: enabling flexible data compression with assist warps (77 citations)
- Exploiting Inter-Warp Heterogeneity to Improve GPGPU Performance (52 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Central processing unit
- Programming language
Mahmut Kandemir mostly deals with Parallel computing, Embedded system, Cache, Scheduling and Dram.
His studies deal with areas such as Kernel, Interleaved memory, Latency and Uniform memory access as well as Parallel computing.
In his research, Mahmut Kandemir undertakes multidisciplinary study on Embedded system and Throughput.
His work on Cache algorithms as part of general Cache study is frequently linked to Video decoder and Performance improvement, therefore connecting diverse disciplines of science.
His work carried out in the field of Scheduling brings together such families of science as Quality of service, Dynamic demand, Queue and Distributed computing.
His Bandwidth research focuses on Schedule and how it relates to Energy consumption and Reduction.
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