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Impact of decoding strategies on GPU energy usage in large language model text generation. [PDF]
Sci RepNik A, Riegler MA, Halvorsen P.
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Survey of Nvidia RTX Technology
Programming and Computer Software, 2020Nvidia 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.
Vadim V. Sanzharov +2 more
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NVIDIA'S Tegra K1 system-on-chip
2014 IEEE Hot Chips 26 Symposium (HCS), 2014Michael Ditty +3 more
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IEEE Micro, 2019
NVIDIA's latest processor family, the Turing GPU, was designed to realize a vision for next-generation graphics combining rasterization, ray tracing, and deep learning. It includes fundamental advancements in several key areas: streaming multiprocessor efficiency, a Tensor Core for accelerated AI inferencing, and an RTCore for accelerated ray tracing ...
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NVIDIA's latest processor family, the Turing GPU, was designed to realize a vision for next-generation graphics combining rasterization, ray tracing, and deep learning. It includes fundamental advancements in several key areas: streaming multiprocessor efficiency, a Tensor Core for accelerated AI inferencing, and an RTCore for accelerated ray tracing ...
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ACM SIGGRAPH 2014 Computer Animation Festival, 2014
FlameWorks is a system for adding realistic fire, smoke, and explosion effects to games. It combines a state-of-the-art grid-based fluid simulator with an efficient volume-rendering system, all optimized to run in real time. It runs entirely on the GPU using DirectX 11.
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FlameWorks is a system for adding realistic fire, smoke, and explosion effects to games. It combines a state-of-the-art grid-based fluid simulator with an efficient volume-rendering system, all optimized to run in real time. It runs entirely on the GPU using DirectX 11.
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NVIDIA Jetson Platform Characterization
2017This study characterizes the NVIDIA Jetson TK1 and TX1 Platforms, both built on a NVIDIA Tegra System on Chip and combining a quad-core ARM CPU and an NVIDIA GPU. Their heterogeneous nature, as well as their wide operating frequency range, make it hard for application developers to reason about performance and determine which optimizations are worth ...
Hassan Halawa +3 more
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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.
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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.
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NVIDIA GPGPUs Instructions Energy Consumption
2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2020In 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 +8 more
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