2018 - IEEE Fellow For contributions to power and reliability management of Systems-on-Chip
Tajana Rosing focuses on Embedded system, System on a chip, Real-time computing, Energy management and Energy consumption. His Embedded system study incorporates themes from Computer hardware, Reliability, State, Power management and Dynamic priority scheduling. The concepts of his System on a chip study are interwoven with issues in Multiprocessing, Electronic engineering and UltraSPARC.
The study incorporates disciplines such as Temperature control and Reliability engineering in addition to Multiprocessing. His Real-time computing research is multidisciplinary, incorporating perspectives in Wind power, Schedule, Data center, Renewable energy and Operations research. His research combines Overhead and Energy consumption.
His scientific interests lie mostly in Embedded system, Efficient energy use, Energy consumption, Real-time computing and Parallel computing. His studies deal with areas such as Workload, Scheduling, Power management and Server as well as Embedded system. His Efficient energy use research incorporates elements of Floating point, Scalability, Quality of service, Bottleneck and Computation.
His Energy consumption research includes themes of Distributed computing and Energy management. The various areas that Tajana Rosing examines in his Real-time computing study include Wireless sensor network, Reliability engineering and Renewable energy. Tajana Rosing combines subjects such as Non-volatile memory, Interleaved memory and Content-addressable memory with his study of Parallel computing.
His primary areas of study are Speedup, Efficient energy use, Artificial intelligence, Artificial neural network and Parallel computing. His research in Speedup intersects with topics in Cluster analysis, Inference, Computer engineering and Memory management. His studies in Efficient energy use integrate themes in fields like Floating point, Scalability, Quality of service, Bottleneck and Computation.
His work is dedicated to discovering how Artificial intelligence, Task are connected with Routing and other disciplines. He has researched Parallel computing in several fields, including Energy consumption, Non-volatile memory, Content-addressable memory and General-purpose computing on graphics processing units. The Energy consumption study which covers Latency that intersects with Embedded system.
The scientist’s investigation covers issues in Speedup, Efficient energy use, Artificial intelligence, Parallel computing and Content-addressable memory. His Speedup research includes elements of Artificial neural network, Computational complexity theory, Inference, Cluster analysis and Memory management. His Efficient energy use research includes themes of Floating point and Computation.
His study looks at the relationship between Artificial intelligence and fields such as Machine learning, as well as how they intersect with chemical problems. His Parallel computing research incorporates elements of Energy consumption, Non-volatile memory, Semiconductor memory and Graph. His work in Energy consumption addresses issues such as Memory architecture, which are connected to fields such as Memory access pattern.
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PDRAM: a hybrid PRAM and DRAM main memory system
Gaurav Dhiman;Raid Ayoub;Tajana Rosing.
design automation conference (2009)
Energy Harvesting for Structural Health Monitoring Sensor Networks
Gyuhae Park;Tajana Rosing;Michael D. Todd;Charles R. Farrar.
Journal of Infrastructure Systems (2008)
Integrating microsecond circuit switching into the data center
George Porter;Richard Strong;Nathan Farrington;Alex Forencich.
acm special interest group on data communication (2013)
Temperature aware task scheduling in MPSoCs
Ayse Kivilcim Coskun;Tajana Simunic Rosing;Keith Whisnant.
design, automation, and test in europe (2007)
Prediction and management in energy harvested wireless sensor nodes
Joaquin Recas Piorno;Carlo Bergonzini;David Atienza;Tajana Simunic Rosing.
international conference on wireless communication, vehicular technology, information theory and aerospace & electronic systems technology (2009)
Utilizing green energy prediction to schedule mixed batch and service jobs in data centers
Baris Aksanli;Jagannathan Venkatesh;Liuyi Zhang;Tajana Rosing.
Operating Systems Review (2012)
Managing distributed ups energy for effective power capping in data centers
Vasileios Kontorinis;Liuyi Eric Zhang;Baris Aksanli;Jack Sampson.
international symposium on computer architecture (2012)
Dynamic thermal management in 3D multicore architectures
Ayse K. Coskun;Jose L. Ayala;David Atienza;Tajana Simunic Rosing.
design, automation, and test in europe (2009)
Application-driven method and apparatus for limiting power consumption in a processor-controlled hardware platform
Andrea Acquaviva;Luca Benini;Tajana S. Rosing.
Dynamic voltage frequency scaling for multi-tasking systems using online learning
Gaurav Dhiman;Tajana Simunic Rosing.
international symposium on low power electronics and design (2007)
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