NVIDIA
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NVIDIA NeMo (Neural Modules) is an open source toolkit for conversational AI. It is built for data scientists and researchers to build new state of the art speech and NLP networks easily through API compatible building blocks that can be connected together.
Omniverse aims for universal interoperability across different applications and 3D ecosystem vendors. It provides efficient real-time scene updates and is based on open-standards and protocols. The Omniverse Platform is designed to act as a hub, enabling new capabilities to be exposed as micro-services to any connected clients and applications.
Quadro is the world preeminent visual computing platform. Trusted by millions of creative and technical professionals to accelerate their workflows, only Quadro has the most advanced ecosystem of hardware, software and tools to transform the disruptive challenges of today into business successes of tomorrow.
NGC is the hub for GPU-optimized software for deep learning, machine learning, and high-performance computing (HPC) that takes care of all the plumbing so data scientists, developers, and researchers can focus on building solutions, gathering insights, and delivering business value.
Gelato is designed for the creation of 3D visual effects and animation in feature films.
NVIDIA DGX™ Cloud is an end-to-end, scalable AI platform for developers, offering scalable capacity built on the latest NVIDIA architecture and co-engineered with the world’s leading cloud service providers (CSPs).
The RAPIDS suite of open source software libraries and APIs gives you the ability to execute end-to-end data science and analytics pipelines entirely on GPUs. Licensed under Apache 2.0, RAPIDS is incubated by NVIDIA® based on extensive hardware and data science science experience. RAPIDS utilizes NVIDIA CUDA® primitives for low-level compute optimization, and exposes GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. RAPIDS also focuses on common data preparation tasks for analytics and data science. This includes a familiar dataframe API that integrates with a variety of machine learning algorithms for end-to-end pipeline accelerations without paying typical serialization costs. RAPIDS also includes support for multi-node, multi-GPU deployments, enabling vastly accelerated processing and training on much larger dataset sizes.
Achieve RTX-accelerated performance on any device, anywhere, with NVIDIA RTX™ Server, a highly flexible reference design that combines high-end NVIDIA® Quadro RTX™ 6000 and 8000 GPUs with NVIDIA virtual GPU (vGPU) software to deliver exceptional compute power. With a range of validated solutions, from virtualization to collaborative design with NVIDIA Omniverse™, RTX Server enables every professional to do their best work wherever they are—at a fraction of the cost, space, and power of CPU-based solutions.
The NVIDIA DGX-1 is a purpose-built deep learning system designed to accelerate AI research and development. Combining powerful hardware with an optimized software stack, it delivers exceptional computational performance, enabling data scientists and researchers to train complex deep neural networks efficiently. The DGX-1 integrates eight NVIDIA Tesla V100 GPUs, interconnected via NVIDIA NVLink, providing up to 1 petaFLOPS of half-precision (FP16 performance. This system is engineered to handle the most demanding AI workloads, offering a turnkey solution that simplifies deployment and accelerates time to insight. Key Features and Functionality: - High-Performance GPUs: Equipped with eight NVIDIA Tesla V100 GPUs, each featuring 32GB of memory, the DGX-1 delivers unparalleled processing power for deep learning tasks. - Advanced Interconnectivity: Utilizes NVIDIA NVLink technology, providing high-speed GPU-to-GPU communication at 300 GB/s per GPU, significantly enhancing data throughput and reducing training times. - Comprehensive Software Stack: Comes pre-installed with the NVIDIA Deep Learning GPU Training System (DIGITS, CUDA Deep Neural Network library (cuDNN, and optimized versions of popular deep learning frameworks such as TensorFlow, PyTorch, and Caffe, facilitating seamless development and deployment of AI models. - Robust Storage and Memory: Features 512GB of system memory and a 7TB SSD deep learning cache, ensuring efficient data handling and storage capabilities. - Scalable Networking: Includes dual 10GbE and quad InfiniBand 100Gb networking interfaces, supporting high-bandwidth data transfer and scalability for large-scale AI projects. Primary Value and Problem Solved: The NVIDIA DGX-1 addresses the computational challenges inherent in deep learning and AI research by providing a fully integrated, high-performance system that accelerates model training and deployment. By delivering the equivalent performance of hundreds of traditional servers in a single unit, the DGX-1 reduces infrastructure complexity, lowers operational costs, and shortens development cycles. This enables organizations to focus on innovation and discovery, transforming vast datasets into actionable insights more rapidly and effectively.
NVIDIA Reviews
Ankit P.
Revolutionary Acceleration for Recommender Systems
Neha J.
High Performance and Scalability for Large Language Models
Dharmik V.
Megatron-LM is a framework and a research project which trains AI models like GPT and BERT.
About
What is NVIDIA?
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.
