What is she best known for?
The fields of study she is best known for:
- Operating system
- Computer network
- Central processing unit
Chita R. Das mostly deals with Embedded system, Computer network, Network on a chip, Distributed computing and Parallel computing.
Her Embedded system study integrates concerns from other disciplines, such as Scalability, Cache, Energy consumption, Exploit and System recovery.
Her Computer network study frequently draws connections between adjacent fields such as Wireless mesh network.
Her Network on a chip research includes themes of Network packet, Throughput, Router, Fault tolerance and System on a chip.
Chita R. Das has researched Distributed computing in several fields, including Mobile ad hoc network, Workload and Processor scheduling.
The Parallel computing study combines topics in areas such as Static memory allocation, Scheduling, Thread and General-purpose computing on graphics processing units.
Her most cited work include:
- Towards characterizing cloud backend workloads: insights from Google compute clusters (326 citations)
- ViChaR: A Dynamic Virtual Channel Regulator for Network-on-Chip Routers (256 citations)
- A novel dimensionally-decomposed router for on-chip communication in 3D architectures (240 citations)
What are the main themes of her work throughout her whole career to date?
Her primary scientific interests are in Computer network, Distributed computing, Parallel computing, Scheduling and Embedded system.
Her work on Wireless ad hoc network expands to the thematically related Computer network.
Chita R. Das usually deals with Distributed computing and limits it to topics linked to Server and Shared resource.
The concepts of her Parallel computing study are interwoven with issues in Scheme and Queueing theory.
The study incorporates disciplines such as Scalability, Latency, Energy consumption, Efficient energy use and Multi-core processor in addition to Embedded system.
Her Router study combines topics in areas such as Throughput, Interconnection and Network on a chip.
She most often published in these fields:
- Computer network (33.65%)
- Distributed computing (31.76%)
- Parallel computing (27.67%)
What were the highlights of her more recent work (between 2013-2021)?
- Parallel computing (27.67%)
- Embedded system (14.78%)
- Scheduling (16.67%)
In recent papers she was focusing on the following fields of study:
Chita R. Das focuses on Parallel computing, Embedded system, Scheduling, Distributed computing and Cache.
Her Parallel computing research is multidisciplinary, relying on both Bottleneck, Interleaved memory and General-purpose computing on graphics processing units.
She interconnects Android, Scalability, Multi-core processor and Central processing unit in the investigation of issues within Embedded system.
Her Scheduling study combines topics from a wide range of disciplines, such as Quality of service, Queue and Server.
Chita R. Das has included themes like Workload, Cloud computing, Efficient energy use and Provisioning in her Distributed computing study.
Chita R. Das studied Cache and Latency that intersect with Garbage collection.
Between 2013 and 2021, her most popular works were:
- Scheduling Techniques for GPU Architectures with Processing-In-Memory Capabilities (108 citations)
- Managing GPU Concurrency in Heterogeneous Architectures (95 citations)
- A case for core-assisted bottleneck acceleration in GPUs: enabling flexible data compression with assist warps (77 citations)
In her most recent research, the most cited papers focused on:
- Operating system
- Computer network
- Central processing unit
Parallel computing, Scheduling, Embedded system, Cache and Latency are her primary areas of study.
Her research in Parallel computing intersects with topics in Dram, Queueing theory, Bottleneck, Kernel and General-purpose computing on graphics processing units.
The Scheduling study combines topics in areas such as Queue, Cloud computing, Server and Datapath.
Her Embedded system research is multidisciplinary, relying on both Android, Key and Virtual desktop.
Her Cache study combines topics from a wide range of disciplines, such as Energy consumption and Video tracking.
Computer network is often connected to Distributed computing in her work.
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