Jason Mars focuses on Distributed computing, Real-time computing, Quality of service, Operating system and Server. His study brings together the fields of Multi-core processor and Distributed computing. His Real-time computing research is multidisciplinary, relying on both Cloud computing and Leverage.
His studies deal with areas such as Mobile device, Mobile computing and Collaborative intelligence as well as Cloud computing. His Quality of service study combines topics in areas such as Boosting and Granularity. Jason Mars combines subjects such as Batch processing and Bubble with his study of Server.
Jason Mars spends much of his time researching Distributed computing, Artificial intelligence, Server, Quality of service and Multi-core processor. Jason Mars brings together Distributed computing and Scale to produce work in his papers. Within one scientific family, he focuses on topics pertaining to Machine learning under Artificial intelligence, and may sometimes address concerns connected to Representation.
His research investigates the connection with Server and areas like Workload which intersect with concerns in Scalability. His Quality of service research incorporates elements of Temporal isolation among virtual machines, Real-time computing, Embedded system and Leverage. His work investigates the relationship between Multi-core processor and topics such as Spec# that intersect with problems in Regression analysis and Predictive modelling.
His primary areas of study are Artificial intelligence, Machine learning, Training set, Dialog box and Training. His primary area of study in Artificial intelligence is in the field of Utterance. His study in Utterance is interdisciplinary in nature, drawing from both Value, Similarity and Natural language processing.
Machine learning combines with fields such as Structure, Control system, Semantic vector and Metric in his work. The study incorporates disciplines such as Annotation and Corpus based in addition to Training set. His Dialog box research is multidisciplinary, incorporating perspectives in Anomaly detection, Data mining and Outlier.
His primary scientific interests are in Dialog box, Benchmark, Information retrieval, Class and Inference. His Dialog box research integrates issues from Anomaly detection, Data mining and Outlier. Jason Mars has researched Benchmark in several fields, including Field and Identification.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Bubble-Up: increasing utilization in modern warehouse scale computers via sensible co-locations
Jason Mars;Lingjia Tang;Robert Hundt;Kevin Skadron.
international symposium on microarchitecture (2011)
Bubble-flux: precise online QoS management for increased utilization in warehouse scale computers
Hailong Yang;Alex Breslow;Jason Mars;Lingjia Tang.
international symposium on computer architecture (2013)
Neurosurgeon: Collaborative Intelligence Between the Cloud and Mobile Edge
Yiping Kang;Johann Hauswald;Cao Gao;Austin Rovinski.
architectural support for programming languages and operating systems (2017)
The impact of memory subsystem resource sharing on datacenter applications
Lingjia Tang;Jason Mars;Neil Vachharajani;Robert Hundt.
international symposium on computer architecture (2011)
Sirius: An Open End-to-End Voice and Vision Personal Assistant and Its Implications for Future Warehouse Scale Computers
Johann Hauswald;Michael A. Laurenzano;Yunqi Zhang;Cheng Li.
architectural support for programming languages and operating systems (2015)
The Architectural Implications of Autonomous Driving: Constraints and Acceleration
Shih-Chieh Lin;Yunqi Zhang;Chang-Hong Hsu;Matt Skach.
architectural support for programming languages and operating systems (2018)
DjiNN and Tonic: DNN as a service and its implications for future warehouse scale computers
Johann Hauswald;Yiping Kang;Michael A. Laurenzano;Quan Chen.
international symposium on computer architecture (2015)
Whare-map: heterogeneity in "homogeneous" warehouse-scale computers
Jason Mars;Lingjia Tang.
international symposium on computer architecture (2013)
Contention aware execution: online contention detection and response
Jason Mars;Neil Vachharajani;Robert Hundt;Mary Lou Soffa.
symposium on code generation and optimization (2010)
SMiTe: Precise QoS Prediction on Real-System SMT Processors to Improve Utilization in Warehouse Scale Computers
Yunqi Zhang;Michael A. Laurenzano;Jason Mars;Lingjia Tang.
international symposium on microarchitecture (2014)
University of Michigan–Ann Arbor
University of Virginia
University of Michigan–Ann Arbor
University of Michigan–Ann Arbor
University of Michigan–Ann Arbor
University of California, San Diego
University of Virginia
University of Michigan–Ann Arbor
University of Virginia
Hong Kong University of Science and Technology
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: