Results 271 to 280 of about 209,152 (323)

Survey of Nvidia RTX Technology

Programming and Computer Software, 2020
Nvidia RTX is a proprietary hardware-accelerated ray tracing technology. Since implementation details are unknown, there were many questions in the development community about the hardware implementation: which stages of the ray tracing pipeline are hardware-accelerated and which of them can be efficiently implemented in software.
V. V. Sanzharov, V. A. Frolov, V. A. Galaktionov   +2 more
openaire   +1 more source

NVIDIA Deep Learning Tutorial

2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2017
Learn how hardware and software stacks enable not only quick prototyping, but also efficient large-scale production deployments. The tutorial will conclude with a discussion about hands-on deep learning training opportunities as well as free academic teaching materials and GPU cloud platforms for university faculty.
openaire   +1 more source

NVIDIA GPGPUs Instructions Energy Consumption

2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2020
In this work, we accurately measure the energy consumption of the different instructions that can be executed in modern NVIDIA GPGPUs. We use three different software techniques to read the GPU on-chip power sensors, which use NVIDIA’s NVML API and provide an in-depth comparison between these techniques.
Yehia Arafa, Ammar ElWazir, Abdelrahman Elkanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed Badawy, Gopinath Chennupati, Stephan Eidenbenz, Nandakishore Santhi   +8 more
openaire   +1 more source

Predicting NVIDIA's Next-Day Stock Price: A Comparative Analysis of LSTM, MLP, ARIMA, and ARIMA-GARCH Models

arXiv.org
Forecasting stock prices remains a considerable challenge in financial markets, bearing significant implications for investors, traders, and financial institutions.
Yiluan Xing, Chao Yan, C. Xie
semanticscholar   +1 more source

NVIDIA Nemotron Nano V2 VL

arXiv.org
We introduce Nemotron Nano V2 VL, the latest model of the Nemotron vision-language series designed for strong real-world document understanding, long video comprehension, and reasoning tasks. Nemotron Nano V2 VL delivers significant improvements over our
Nvidia Amala Sanjay Deshmukh, Kateryna Chumachenko, Tuomas Rintamaki, Matthieu Le, Tyler Poon, Danial Mohseni Taheri, Ilia Karmanov, Guilin Liu, Jarno Seppanen, Guo Chen, Karan Sapra, Zhi-Wei Yu, Adi Renduchintala, Charles Wang, Peter Jin, Arushi Goel, Mike Ranzinger, Lukas Voegtle, Philipp Fischer, Timo Roman, Wei Ping, Bo Wang, Zhuolin Yang, Nayeon Lee, Shaokun Zhang, Fuxiao Liu, Zhiqi Li, Di Zhang, Gregorio Heinrich, Hongxu Yin, Song Han, Pavlo Molchanov, Parth Mannan, Yaohui Xu, Jane Polak Scowcroft, Tom Balough, Subhashree Radhakrishnan, Paris Zhang, Sean Cha, Ratnesh Kumar, Zaid Pervaiz Bhat, Jian Zhang, Darragh Hanley, Pritam Biswas, J. Oliver, Kevin Vasques, Roger Waleffe, Duncan Riach, Oluwatobi Olabiyi, Ameya Sunil Mahabaleshwarkar, Bilal Kartal, Pritam Gundecha, Khanh Nguyen, Alexandre Milesi, Eugene Khvedchenia, Ran Zilberstein, Ofri Masad, Natan Bagrov, Nave Assaf, Tomer Asida, Daniel Afrimi, Amit Zuker, Netanel Haber, Zhiyu Cheng, Jingyu Xin, Di Wu, Nik Spirin, Maryam Moosaei, Roman Ageev, Vanshil Atul Shah, Yuting Wu, Daniel Korzekwa, Unnikrishnan Kizhakkemadam Sreekumar, Wanli Jiang, Padmavathy Subramanian, Alejandra Rico, Sandip Bhaskar, Saeid Motiian, Kedi Wu, Annie Surla, Chia-Chih Chen, Hayden Wolff, Matthew I. Feinberg, Melissa Corpuz, Marek Wawrzos, E. Long, Aastha Jhunjhunwala, Paul Hendricks, Farzan Memarian, Benika Hall, Xin-Yu Wang, David Mosallanezhad, Soumye Singhal, L. Vega, Katherine Cheung, Krzysztof Pawelec, Michael Evans, K. Luna, Jie Lou, Erick Galinkin, Akshay Hazare, Kaustubh Purandare, Ann Guan, Anna Warno, Chen Cui, Yoshi Suhara, Shibani Likhite, Seph Mard, M. Price, Laya Sleiman, Saori Kaji, Udi Karpas, Kari Briski, Joey Conway, Michael Lightstone, Jan Kautz, Mohammad Shoeybi, Mostofa Patwary, Jonathen Cohen, Oleksii Kuchaiev, Andrew Tao, Bryan Catanzaro   +121 more
semanticscholar   +1 more source

NVIDIA Grace Superchip Early Evaluation for HPC Applications

HPC Asia Workshops
Arm-based system in HPC are a reality since more than a decade. However, when a new chip enters the market always implies challenges, not only at ISA level, but also with regards to the SoC integration, the memory subsystem, the board integration, the ...
Fabio Banchelli, Joan Vinyals-Ylla-Catala, Josep Pocurull, Marc Clascà, Kilian Peiro, Filippo Spiga, M. Garcia-Gasulla, Filippo Mantovani   +7 more
semanticscholar   +1 more source

Bringing Auto-tuning to HIP: Analysis of Tuning Impact and Difficulty on AMD and Nvidia GPUs

European Conference on Parallel Processing
Many studies have focused on developing and improving auto-tuning algorithms for Nvidia Graphics Processing Units (GPUs), but the effectiveness and efficiency of these approaches on AMD devices have hardly been studied.
Milo Lurati, Stijn Heldens, A. Sclocco, B. V. Werkhoven   +3 more
semanticscholar   +1 more source

NVBit: A Dynamic Binary Instrumentation Framework for NVIDIA GPUs

Micro, 2019
Binary instrumentation frameworks are widely used to implement profilers, performance evaluation, error checking, and bug detection tools. While dynamic binary instrumentation tools such as PIN and DynamoRio are supported on CPUs, GPU architectures ...
Oreste Villa, M. Stephenson, D. Nellans, S. Keckler   +3 more
semanticscholar   +1 more source

Understanding NVIDIA GPGPU Hardware

2013
This chapter presents NVIDIA general purpose graphical processing unit (GPGPU) architecture, by detailing both hardware and software concepts. The evolution of GPGPUs from the beginning to the most modern GPGPUs is presented in order to illustrate the trends that motivate the changes that occurred during this evolution.
openaire   +1 more source

Administering NVIDIA Jetson Nano

2020
The NVIDIA Jetson Nano device is a mini computer with high-end features and GPU capabilities. The board system consists of hardware and software. In this chapter, you will learn to manage the NVIDIA Jetson Nano with administration software.
openaire   +1 more source