Zobrazeno 1 - 10
of 64
pro vyhledávání: '"LINGJIA TANG"'
Autor:
Jason Mars, Yiping Kang, Roland Daynauth, Baichuan Li, Ashish Mahendra, Krisztian Flautner, Lingjia Tang
Publikováno v:
IEEE Computer Architecture Letters. :1-4
Publikováno v:
ACM Transactions on Architecture and Code Optimization. 16:1-25
We introduce Caliper , a technique for accurately estimating performance interference occurring in shared servers. Caliper overcomes the limitations of prior approaches by leveraging a micro-experiment-based technique. In contrast to state-of-the-art
Publikováno v:
Optik. 178:1071-1078
In this paper, a non-iterative large-solution-area fluorescence-lifetime-extraction algorithm applying to the mono-exponential model have been proposed. This algorithm consists of two parts. One is a preprocessing of the decay histogram through first
Publikováno v:
MICRO
With the growing popularity of cloud gaming and cloud virtual reality (VR), interactive 3D applications have become a major class of workloads for the cloud. However, despite their growing importance, there is limited public research on how to design
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f8fbe5c9cebe758c83d41f68734047ed
Publikováno v:
ASPLOS
With the ever growing popularity of cloud computing and web services, Internet companies are in need of increased computing capacity to serve the demand. However, power has become a major limiting factor prohibiting the growth in industry: it is ofte
Autor:
Ronald G. Dreslinski, Michael A. Laurenzano, David Meisner, Lingjia Tang, Jason Mars, Yunqi Zhang, Thomas F. Wenisch, Chang-Hong Hsu
Publikováno v:
ACM Transactions on Computer Systems. 35:1-33
Reducing the long tail of the query latency distribution in modern warehouse scale computers is critical for improving performance and quality of service (QoS) of workloads such as Web Search and Memcached. Traditional turbo boost increases a process
Autor:
Jason Mars, Johann Hauswald, Parker Hill, Michael A. Laurenzano, Stefan Larson, Lingjia Tang, Jonathan K. Kummerfeld, Andrew Lee, Anish Mahendran
Publikováno v:
NAACL-HLT (1)
In a corpus of data, outliers are either errors: mistakes in the data that are counterproductive, or are unique: informative samples that improve model robustness. Identifying outliers can lead to better datasets by (1) removing noise in datasets and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::40c3f71aae02474cb2ef9b5ccd24156b
http://arxiv.org/abs/1904.03122
http://arxiv.org/abs/1904.03122
Autor:
Jason Mars, Lingjia Tang, Ram Srivatsa Kannan, Jeongseob Ahn, Lavanya Subramanian, Ashwin Raju
Publikováno v:
EuroSys
The microservice architecture has dramatically reduced user effort in adopting and maintaining servers by providing a catalog of functions as services that can be used as building blocks to construct applications. This has enabled datacenter operator
Publikováno v:
HPCA
Autor:
Jason Mars, Jonathan K. Kummerfeld, Joseph Peper, Anish Mahendran, Andrew Lee, Lingjia Tang, Kevin Leach, Michael A. Laurenzano, Stefan Larson, Christopher Clarke, Parker Hill
Publikováno v:
EMNLP/IJCNLP (1)
Task-oriented dialog systems need to know when a query falls outside their range of supported intents, but current text classification corpora only define label sets that cover every example. We introduce a new dataset that includes queries that are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26f395a7eddd6eb0fc8df71e1cd98b3c