Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Chien, Steven W. D."'
Cloud applications need network data encryption to isolate from other tenants and protect their data from potential eavesdroppers in the network infrastructure. This paper presents SDT, a protocol design for emerging datacenter transport protocols to
Externí odkaz:
http://arxiv.org/abs/2406.15686
Autor:
Chien, Steven W. D., Sato, Kento, Podobas, Artur, Jansson, Niclas, Markidis, Stefano, Honda, Michio
We have seen an increase in the heterogeneity of storage technologies potentially available to scientific applications, such as burst buffers, managed cloud parallel file systems (PFS), and object stores. However, those applications cannot easily uti
Externí odkaz:
http://arxiv.org/abs/2401.14576
One of the most promising approaches for data analysis and exploration of large data sets is Machine Learning techniques that are inspired by brain models. Such methods use alternative learning rules potentially more efficiently than established lear
Externí odkaz:
http://arxiv.org/abs/2107.06676
Autor:
Podobas, Artur, Svedin, Martin, Chien, Steven W. D., Peng, Ivy B., Ravichandran, Naresh Balaji, Herman, Pawel, Lansner, Anders, Markidis, Stefano
The modern deep learning method based on backpropagation has surged in popularity and has been used in multiple domains and application areas. At the same time, there are other -- less-known -- machine learning algorithms with a mature and solid theo
Externí odkaz:
http://arxiv.org/abs/2106.05373
For many, Graphics Processing Units (GPUs) provides a source of reliable computing power. Recently, Nvidia introduced its 9th generation HPC-grade GPUs, the Ampere 100, claiming significant performance improvements over previous generations, particul
Externí odkaz:
http://arxiv.org/abs/2106.04979
Autor:
Chien, Steven W. D., Nylund, Jonas, Bengtsson, Gabriel, Peng, Ivy B., Podobas, Artur, Markidis, Stefano
Large-scale simulations of plasmas are essential for advancing our understanding of fusion devices, space, and astrophysical systems. Particle-in-Cell (PIC) codes have demonstrated their success in simulating numerous plasma phenomena on HPC systems.
Externí odkaz:
http://arxiv.org/abs/2008.04397
Machine Learning applications on HPC systems have been gaining popularity in recent years. The upcoming large scale systems will offer tremendous parallelism for training through GPUs. However, another heavy aspect of Machine Learning is I/O, and thi
Externí odkaz:
http://arxiv.org/abs/2008.04395
CUDA Unified Memory improves the GPU programmability and also enables GPU memory oversubscription. Recently, two advanced memory features, memory advises and asynchronous prefetch, have been introduced. In this work, we evaluate the new features on t
Externí odkaz:
http://arxiv.org/abs/1910.09598
Autor:
Olshevsky, Vyacheslav, Khotyaintsev, Yuri V., Lalti, Ahmad, Divin, Andrey, Delzanno, Gian Luca, Anderzen, Sven, Herman, Pawel, Chien, Steven W. D., Avanov, Levon, Dimmock, Andrew P., Markidis, Stefano
We investigate the properties of the ion sky maps produced by the Dual Ion Spectrometers (DIS) from the Fast Plasma Investigation (FPI). We have trained a convolutional neural network classifier to predict four regions crossed by the MMS on the daysi
Externí odkaz:
http://arxiv.org/abs/1908.05715
Floating-point operations can significantly impact the accuracy and performance of scientific applications on large-scale parallel systems. Recently, an emerging floating-point format called Posit has attracted attention as an alternative to the stan
Externí odkaz:
http://arxiv.org/abs/1907.05917