Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Rajkishore Barik"'
Publikováno v:
Languages and Compilers for Parallel Computing ISBN: 9783030727888
LCPC
LCPC
Convolutional Neural Networks (CNNs) are ubiquitous in applications ranging from self-driving cars to various branches of health care. CPUs with large core counts and wide SIMD support are used in HPC clusters and supercomputers; therefore, high-perf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f33b402f276c85a9e67579b8d0863842
https://doi.org/10.1007/978-3-030-72789-5_9
https://doi.org/10.1007/978-3-030-72789-5_9
Publikováno v:
ICSE (SEIP)
Feature flags are commonly used in mobile app development and can introduce technical debt related to deleting their usage from the codebase. This can adversely affect the overall reliability of the apps and increase their maintenance complexity. Red
Title:Optimization of Swift Protocols Abstract: Swift, an increasingly-popular programming language, advocates the use of protocols, which define a set of required methods and properties for conforming types. Protocols are commonly used in Swift prog
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::210a39a0163dafa69b61f168f5a4f357
Autor:
Tatiana Shpeisman, Geoff Lowney, Rajkishore Barik, Hongbo Rong, Paul Petersen, Victor W. Lee, Todd A. Anderson, Chunling Hu, Hai Liu, Greg Henry, Youfeng Wu
Publikováno v:
Languages and Compilers for Parallel Computing ISBN: 9783030352240
LCPC
LCPC
Current processor trend is to couple a commodity processor with a GPU, a co-processor, or an accelerator. To unleash the full computational power of such heterogeneous systems is a daunting task: programmers often resort to heterogeneous scheduling r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ec3a1af1ab3739bbfd3411db89b2a16
https://doi.org/10.1007/978-3-030-35225-7_13
https://doi.org/10.1007/978-3-030-35225-7_13
Autor:
Vanish Talwar, Rajkishore Barik, Yuan Chen, Brian T. Lewis, Karsten Schwan, Naila Farooqui, Tatiana Shpeisman, Indrajit Roy
Publikováno v:
International Journal of Parallel Programming. 46:336-375
Integrated GPU systems are a cost-effective and energy-efficient option for accelerating data-intensive applications. While these platforms have reduced overhead of offloading computation to the GPU and potential for fine-grained resource scheduling,
Autor:
Rajkishore Barik, Tatiana Shpeisman, Ehsan Totoni, Chick Markley, Armando Fox, Hai Liu, Leonard Truong
Publikováno v:
PLDI
Deep neural networks (DNNs) have undergone a surge in popularity with consistent advances in the state of the art for tasks including image recognition, natural language processing, and speech recognition. The computationally expensive nature of thes
Publikováno v:
Euro-Par 2018: Parallel Processing ISBN: 9783319969824
Euro-Par
Euro-Par
Convolutional Neural Networks (CNNs) represent a class of Deep Neural Networks that is growing in importance due to their state-of-the-art performance in pattern recognition tasks in various domains, including image recognition, speech recognition, a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f48183811495b7d3f3c5bda671fc04f4
https://doi.org/10.1007/978-3-319-96983-1_19
https://doi.org/10.1007/978-3-319-96983-1_19
Publikováno v:
ACM Transactions on Architecture and Code Optimization. 10:1-24
Register allocation is an essential optimization for all compilers. A number of sophisticated register allocation algorithms have been developed over the years. The two fundamental classes of register allocation algorithms used in modern compilers ar
Autor:
V. Krishna Nandivada, Rajkishore Barik
Publikováno v:
ACM Transactions on Architecture and Code Optimization. 10:1-22
Bitwidth-aware register allocation has caught the attention of researchers aiming to effectively reduce the number of variables spilled into memory. For general-purpose processors, this improves the execution time performance and reduces runtime memo
Autor:
Anand Venkat, Mahdi Soltan Mohammadi, Jongsoo Park, Hongbo Rong, Rajkishore Barik, Michelle Mills Strout, Mary Hall
Publikováno v:
SC16: International Conference for High Performance Computing, Networking, Storage and Analysis.