What is he best known for?
The fields of study he is best known for:
- Operating system
- Central processing unit
- Computer network
Ravi Iyer focuses on Cache, Operating system, Quality of service, Cache coloring and Cache algorithms.
His work deals with themes such as Memory architecture, Embedded system, Shared memory and Static random-access memory, which intersect with Cache.
His Memory architecture research includes elements of Computer network and Memory bandwidth.
His Embedded system study combines topics in areas such as Multi-core processor and Router.
His Virtualization, Server and Workload study are his primary interests in Operating system.
His research in Quality of service tackles topics such as Virtual machine which are related to areas like Distributed computing and Scheduling.
His most cited work include:
- CQoS: a framework for enabling QoS in shared caches of CMP platforms (256 citations)
- QoS policies and architecture for cache/memory in CMP platforms (244 citations)
- TCP onloading for data center servers (165 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Cache, Operating system, Embedded system, Computer network and Server.
His Cache study is concerned with the larger field of Parallel computing.
The study incorporates disciplines such as Internet protocol suite, Multi-core processor and Router in addition to Embedded system.
The various areas that Ravi Iyer examines in his Computer network study include Internet Protocol and Crossbar switch.
Non-uniform memory access is closely connected to Shared memory in his research, which is encompassed under the umbrella topic of Virtual machine.
His Virtualization study integrates concerns from other disciplines, such as Quality of service and Translation lookaside buffer.
He most often published in these fields:
- Cache (34.78%)
- Operating system (29.57%)
- Embedded system (24.35%)
What were the highlights of his more recent work (between 2015-2021)?
- Cache (34.78%)
- Parallel computing (11.30%)
- Static random-access memory (6.09%)
In recent papers he was focusing on the following fields of study:
Ravi Iyer mostly deals with Cache, Parallel computing, Static random-access memory, Computer network and Real-time computing.
His research in Cache intersects with topics in Scalability, Artificial neural network, Random access memory, Convolutional neural network and Reinforcement learning.
His work in the fields of Cache-only memory architecture and Massively parallel overlaps with other areas such as Computation.
In his study, Latency is inextricably linked to Xeon, which falls within the broad field of Cache-only memory architecture.
His study in the fields of Virtual network and Resource allocation under the domain of Computer network overlaps with other disciplines such as Telemetry and Service provider.
His Real-time computing research incorporates themes from Mobile computing and Video processing.
Between 2015 and 2021, his most popular works were:
- Neural cache: bit-serial in-cache acceleration of deep neural networks (103 citations)
- Cache QoS: From concept to reality in the Intel® Xeon® processor E5-2600 v3 product family (73 citations)
- Race-to-sleep + content caching + display caching: a recipe for energy-efficient video streaming on handhelds (20 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Central processing unit
- Computer network
His primary scientific interests are in Cache, Random access memory, Convolutional neural network, Artificial neural network and Massively parallel.
His study in Cache is interdisciplinary in nature, drawing from both Real-time computing, Mobile computing and Video processing.
His biological study spans a wide range of topics, including Redundancy and Overhead.
The Convolutional neural network study combines topics in areas such as Bit-serial architecture and Xeon.
His Massively parallel research includes themes of Pooling, Static random-access memory and Cache-only memory architecture.
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