Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Panruo Wu"'
Publikováno v:
Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming.
Publikováno v:
IEEE transactions on visualization and computer graphics.
Large-scale structures have been observed in many shear flows which are the fluid generated between two surfaces moving with different velocity. A better understanding of the physics of the structures (especially large-scale structures) in shear flow
Autor:
Shaoshuai Zhang, Panruo Wu
Publikováno v:
ICPP
Out-of-core processing aims to handle large amount of data when the memory is limited. There exists several out-of-core applications including disk-memory and CPU-GPU processing. Ideally, these out-of-core applications can be expected to be close to
Autor:
Mark Gates, Panruo Wu, Maksims Abalenkovs, Azzam Haidar, David Stevens, Negin Bagherpour, Piotr Luszczek, Ichitaro Yamazaki, Jack Dongarra, Jakub Kurzak, Asim YarKhan, Samuel D. Relton, Mawussi Zounon, Jakub Šístek, Sven Hammarling
Publikováno v:
ACM Transactions on Mathematical Software. 45:1-35
The recent version of the Parallel Linear Algebra Software for Multicore Architectures (PLASMA) library is based on tasks with dependencies from the OpenMP standard. The main functionality of the library is presented. Extensive benchmarks are targete
Publikováno v:
ScalA@SC
Encouraged by the requirement of high speed matrix computations and training deep neural networks, TensorCore was introduced in NVIDIA GPU to further accelerate matrix-matrix multiplication. It supports very fast half precision general matrix matrix
Publikováno v:
ICS
This paper explores the use of Tensor Engines to accelerate nonlinear and linear SVM training. Support Vector Machine(SVM) is a classical machine learning model for classification and regression and remains to be the state-of-the-art model for some t
Publikováno v:
HPDC
Fueled by the surge of ever expanding successful applications of deep neural networks and the great computational power demanded, modern computer processors and accelerators are beginning to offer half precision floating point arithmetic support, and
Publikováno v:
SoCC
Serverless computing is increasingly being used for parallel computing, which have traditionally been implemented as stateful applications. Executing complex, burst-parallel, directed acyclic graph (DAG) jobs poses a major challenge for serverless ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d15f58a475e12f2660d71040700b0577
Publikováno v:
IEEE BigData
Kernel Support Vector Machine (SVM) is a popular machine learning model for classification and regression. A significant challenge of large scale Kernel SVM is the size of the Gram matrix $(n \times n)$, which cannot be stored or processed efficientl