NVIDIA A30 Tensor Core GPUs provide increased performance for every enterprise workload. It enables secure speedups across different workloads, including AI inference at scale and high-performance computing (HPC) applications, thanks to NVIDIA Ampere architecture Tensor Cores and Multi-Instance GPU (MIG). A30 allows an elastic data center and delivers maximum value for organizations by combining rapid …
The atmospheres of distant planets have been described in unprecedented depth in a report published today. Scientists investigated 25 exoplanets (planets that orbit stars outside our solar system) in an effort to learn more about the universe. To be more specific, scientists looked at exoplanets with temperatures over 3,000 degrees Fahrenheit, common on hot Jupiters, …
For the 14th consecutive year, NVIDIA technologies were used in every Academy Award nominee for Best Visual Effects. Five nominees have been announced for the 94th Academy Awards, which will be held on Sunday, March 27: Dune Free Guy No Time to Die Shang-Chi and the Legend of the Ten Rings Spider-Man: No Way Home …
With the NVIDIA A16, you can take remote work to the next level. It enables virtual desktops and workstations with the power and performance to tackle any project from anywhere when used with NVIDIA Virtual PC (vPC) or NVIDIA RTX Virtual Workstation (vWS) software. The NVIDIA Ampere architecture, designed specifically for high-density, graphics-rich virtual desktop …
The NVIDIA A2 Tensor Core GPU enables low-power, small-footprint inference for NVIDIA AI at the edge. With a low-profile PCIe Gen4 card and a configurable thermal design power (TDP) of 40-60W, the A2 accelerates inference in any server for large-scale deployment. Up to a 20-fold increase in inference performance AI inference is used to improve …
Dynamic programming, which is used in algorithms for genomics, quantum computing, route optimization, and more, can be sped up by up to 40% with new DPX instructions in the NVIDIA Hopper GPU architecture that was shown off today at GTC. An instruction set built into NVIDIA H100 GPUs called DPX will help developers write code …
Training the largest AI models can take months on today’s computing platforms. For businesses, that is too slow. The complexity of AI, high-performance computing, and data analytics is increasing, with some models, such as large language models, containing trillions of parameters. The NVIDIA Hopper architecture was designed from the ground up to speed up these …
The NVIDIA H100 is based on the Hopper architecture and serves as the “new engine of the world’s artificial intelligence infrastructures.” AI applications such as speech, conversation, customer service, and recommenders fundamentally reshape data center design. AI data centers process mountains of continuous data to train and refine AI models. Raw data is ingested, refined, …
Machine learning and data analytics are two examples of data-hungry workloads. Enterprises require accelerated servers that are optimized for high performance to handle these compute-intensive tasks. Intel’s new 3rd Gen Intel Xeon Scalable processors (code-named “Ice Lake”) are based on a new architecture that allows for a significant increase in performance and scalability. These new …
MIG is supported in Nvidia A100 build 600061. Build 600297 is compatible with DCGM 2.1.7 and CUDA 11.2. A100 also necessitates the use of CUDA 11. LSF build 600061 and LSF build 600297 must be installed to take advantage of all the features of A100.
By applying new technology to the study of ancient history, researchers hope to improve their understanding of dinosaurs through the use of a new artificial intelligence system. The work, published in Frontiers in Earth Science, scans and evaluates dinosaur fossils using high-resolution Computed Tomography (CT) imaging paired with deep learning models. The discovery is a …
It is said that you can write faster code in C++, but code faster in Python.” Because of CUDA, C and C++ programmers have been able to get the most out of NVIDIA GPUs for more than a decade. More recently, libraries like CuPy and PyTorch made it easier for people who write interpreted languages …
MIG is only compatible with Linux distributions that support CUDA 11/R450 or higher. It’s also a good idea to use the NVIDIA Datacenter Linux driver version 450.80.02 or higher. MIG is not supported on any Windows Pro or Server OS. The new Multi-Instance GPU (MIG) functionality allows NVIDIA Ampere-based GPUs (such as the NVIDIA A100) …
NVIDIA GPUs and CUDA grew substantially in performance and capabilities during the early stages of CUDA support in NAMD. One of the first CUDA-accelerated applications was NAMD, a widely used parallel molecular dynamics simulation engine. For more details, read Using Graphics Processors to Accelerate Molecular Modeling Applications and Adapting a Message-Driven Parallel Application to GPU-Accelerated …
For the first time ever in medicine, a robot operated on a patient during a laparoscopic procedure without the assistance of a surgeon’s hand. An article in Science Robotics describes the development of an improved Smart Tissue Autonomous Robot (STAR) that was successful in completing a difficult task on a pig’s soft tissue. An important …