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Twitch OBS and NVIDIA announce multi-encode livestreaming

Twitch OBS and NVIDIA announce multi-encode livestreaming

The world of livestreaming is on the brink of a significant shift, thanks to a collaborative effort from industry giants Twitch, OBS, and NVIDIA. They have come together to introduce a new feature that is currently in its beta phase, known as Twitch Enhanced Broadcasting. This development is poised to change the way streamers connect with their audiences, offering a more inclusive and adaptable viewing experience.

At the heart of this new feature are the GeForce RTX GPUs, which empower streamers to broadcast their content in multiple resolutions, with 1080p being the highest currently available. This means that regardless of whether viewers are tuning in through a high-speed fiber connection or a more modest mobile network, they will be able to enjoy a seamless streaming experience. The technology is not just about the present; it’s also looking ahead, preparing to support even higher bit rates and resolutions, potentially up to 4K, and the ability to handle up to five streams at once.

The future of video encoding is also an exciting aspect of this initiative. With the introduction of new codecs like AV1 and HEVC, viewers can expect high-quality video that doesn’t consume as much data, making streams more accessible without compromising on visual fidelity. The NVENC encoder, a critical component of GeForce RTX and GTX GPUs, plays a vital role in this process. It ensures that streams are of high quality while keeping the impact on system performance to a minimum.

Today many streamers must choose between higher resolution and reliable streaming. High-quality video provides more enjoyable viewing experiences but causes streams to buffer for viewers with low bandwidth or older viewing devices. Streaming lower-bitrate video allows more people to watch the content seamlessly, but introduces artifacts.

For content creators, the integration process with OBS has been designed to be as smooth as possible. Twitch Enhanced Broadcasting is engineered to automatically fine-tune OBS encoder settings, which means streamers can dedicate more time to engaging with their audience instead of fiddling with complex technical settings.

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What is multi-encode livestreaming

Multi-encode livestreaming refers to the process of encoding a live video stream into multiple bitrates and resolutions simultaneously. This technique is essential for optimizing the viewing experience across various devices and internet speeds. Here’s a breakdown of its key aspects:

  • Encoding Process: Encoding is the conversion of raw video files into a digital format suitable for streaming. In multi-encode livestreaming, this process occurs in several different quality levels (bitrates and resolutions) at once.
  • Adaptive Bitrate Streaming (ABS): This is often used in conjunction with multi-encode livestreaming. ABS allows the video player to dynamically switch between different quality streams based on the viewer’s internet speed. For example, someone with a high-speed connection might receive a high-definition stream, while another with a slower connection gets a lower-resolution version.
  • Benefits:
    • Improved Accessibility: Viewers with varying internet speeds can access the content without constant buffering.
    • Enhanced User Experience: Provides a smooth viewing experience as it can dynamically adjust to the best possible quality.
  • Technical Requirements:
    • Processing Power: Multi-encoding is resource-intensive, requiring significant processing power.
    • Bandwidth: Broadcasting multiple streams simultaneously demands more bandwidth.
  • Applications: It’s widely used in various platforms like YouTube, Twitch, and other streaming services, especially for live events, gaming, webinars, and educational content.

Those eager to be at the forefront of this technological shift can sign up for the beta on a first-come, first-served basis. It’s advisable to register promptly to secure a spot, and upon doing so, instructions will be sent via email on how to start utilizing Twitch Enhanced Broadcasting.

AV1 vs H.264

Both are video codecs, but they differ in their efficiency and application. Here’s an overview:

  • Background:
    • H.264 (AVC): Introduced in 2003, H.264 has been the standard for video compression for many years. It’s widely compatible with various devices and platforms.
    • AV1: A newer codec, developed by the Alliance for Open Media, released in 2018. It’s designed to be more efficient and open-source.
  • Efficiency:
    • Compression: AV1 is more efficient in terms of compression compared to H.264. It can compress video files to a smaller size while maintaining the same quality, or provide better quality at the same file size.
    • Bandwidth Reduction: For streaming platforms, AV1 can significantly reduce bandwidth requirements. This is crucial for reducing costs and improving streaming quality, especially at higher resolutions like 4K.
  • Performance:
    • Encoding Time: AV1’s advanced compression techniques come with a trade-off in encoding time and computational resources. It requires more processing power and time to encode compared to H.264.
    • Decoding: While AV1 decoders are becoming more widespread, H.264 still has broader compatibility, especially in older devices.
  • Adoption and Support:
    • Industry Adoption: AV1 is gaining traction, with support from major companies like Google, Netflix, and Amazon. However, H.264 remains ubiquitous due to its long-standing presence and compatibility.
    • Hardware Acceleration: Newer devices are beginning to include hardware support for AV1, which will reduce the decoding burden and promote wider adoption.
  • Use Cases:
    • H.264: Still preferred for legacy systems or where compatibility is a key concern.
    • AV1: Ideal for high-resolution streaming services, future-proofing content, and where bandwidth efficiency is critical.

This collaboration is set to redefine the standards of livestreaming. By harnessing the capabilities of GeForce RTX GPUs for multi-encode streaming, the initiative is not just about elevating the quality of streams. It’s also about expanding the reach of content to viewers, no matter their hardware or internet limitations, ensuring that everyone can enjoy a high-quality streaming experience. As the beta progresses, those who sign up can look forward to being part of a significant shift in how live content is shared and consumed.

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65 ExaFLOP AI Supercomputer being built by AWS and NVIDIA

65 ExaFLOP AI Supercomputer being built by AWS and NVIDIA

As the artificial intelligence explosion continues the demand for more advanced artificial intelligence (AI) infrastructure continues to grow. In response to this need, Amazon Web Services (AWS) and NVIDIA have expanded their strategic collaboration to provide enhanced AI infrastructure and services by building a new powerful AI Supercomputer capable of providing 65 ExaFLOPs  of processing power.

This partnership aims to integrate the latest technologies from both companies to drive AI innovation to new heights. One of the key aspects of this collaboration is AWS becoming the first cloud provider to offer NVIDIA GH200 Grace Hopper Superchips. These superchips come equipped with multi-node NVLink technology, a significant step forward in AI computing. The GH200 Grace Hopper Superchips present up to 20 TB of shared memory, a feature that can power terabyte-scale workloads, a capability that was previously unattainable in the cloud.

New AI Supercomputer under construction

In addition to hardware advancements, the partnership extends to cloud services. NVIDIA and AWS are set to host NVIDIA DGX Cloud, NVIDIA’s AI-training-as-a-service platform, on AWS. This service will feature the GH200 NVL32, providing developers with the largest shared memory in a single instance. This collaboration will allow developers to access multi-node supercomputing for training complex AI models swiftly, thereby streamlining the AI development process.

65 ExaFLOP of processing power

The partnership between AWS and NVIDIA also extends to the ambitious Project Ceiba. This project aims to design the world’s fastest GPU-powered AI supercomputer. AWS will host this supercomputer, which will primarily serve NVIDIA’s research and development team. The integration of the Project Ceiba supercomputer with AWS services will provide NVIDIA with a comprehensive set of AWS capabilities for research and development, potentially leading to significant advancements in AI technology. Here are some other articles you may find of interest on the subject of AI supercomputers :

Summary of collaboration

  • AWS will be the first cloud provider to bring NVIDIA GH200 Grace Hopper Superchips with new multi-node NVLink technology to the cloud. The NVIDIA GH200 NVL32 multi-node platform connects 32 Grace Hopper Superchips with NVIDIA NVLink and NVSwitch technologies into one instance. The platform will be available on Amazon Elastic Compute Cloud (Amazon EC2) instances connected with Amazon’s powerful networking (EFA), supported by advanced virtualization (AWS Nitro System), and hyper-scale clustering (Amazon EC2 UltraClusters), enabling joint customers to scale to thousands of GH200 Superchips.
  • NVIDIA and AWS will collaborate to host NVIDIA DGX Cloud—NVIDIA’s AI-training-as-a-service—on AWS. It will be the first DGX Cloud featuring GH200 NVL32, providing developers the largest shared memory in a single instance. DGX Cloud on AWS will accelerate training of cutting-edge generative AI and large language models that can reach beyond 1 trillion parameters.
  • NVIDIA and AWS are partnering on Project Ceiba to design the world’s fastest GPU-powered AI supercomputer—an at-scale system with GH200 NVL32 and Amazon EFA interconnect hosted by AWS for NVIDIA’s own research and development team. This first-of-its-kind supercomputer—featuring 16,384 NVIDIA GH200 Superchips and capable of processing 65 exaflops of AI—will be used by NVIDIA to propel its next wave of generative AI innovation.
  • AWS will introduce three additional new Amazon EC2 instances: P5e instances, powered by NVIDIA H200 Tensor Core GPUs, for large-scale and cutting-edge generative AI and HPC workloads, and G6 and G6e instances, powered by NVIDIA L4 GPUs and NVIDIA L40S GPUs, respectively, for a wide set of applications such as AI fine-tuning, inference, graphics and video workloads. G6e instances are particularly suitable for developing 3D workflows, digital twins and other applications using NVIDIA Omniverse, a platform for connecting and building generative AI-enabled 3D applications.
  • “AWS and NVIDIA have collaborated for more than 13 years, beginning with the world’s first GPU cloud instance. Today, we offer the widest range of NVIDIA GPU solutions for workloads including graphics, gaming, high performance computing, machine learning, and now, generative AI,” said Adam Selipsky, CEO at AWS. “We continue to innovate with NVIDIA to make AWS the best place to run GPUs, combining next-gen NVIDIA Grace Hopper Superchips with AWS’s EFA powerful networking, EC2 UltraClusters’ hyper-scale clustering, and Nitro’s advanced virtualization capabilities.”

Amazon NVIDIA partner

To further bolster its AI offerings, AWS is set to introduce three new Amazon EC2 instances powered by NVIDIA GPUs. These include the P5e instances, powered by NVIDIA H200 Tensor Core GPUs, and the G6 and G6e instances, powered by NVIDIA L4 GPUs and NVIDIA L40S GPUs, respectively. These new instances will enable customers to build, train, and deploy their cutting-edge models on AWS, thereby expanding the possibilities for AI development.

AWS NVIDIA DGX Cloud hosting

Furthermore, AWS will host the NVIDIA DGX Cloud powered by the GH200 NVL32 NVLink infrastructure. This service will provide enterprises with fast access to multi-node supercomputing capabilities, enabling them to train complex AI models efficiently.

To boost generative AI development, NVIDIA has announced software on AWS, including the NVIDIA NeMo Retriever microservice and NVIDIA BioNeMo. These tools will provide developers with the resources they need to explore new frontiers in AI development.

The expanded collaboration between AWS and NVIDIA represents a significant step forward in AI innovation. By integrating their respective technologies, these companies are set to provide advanced infrastructure, software, and services for generative AI innovations. The partnership will not only enhance the capabilities of AI developers but also pave the way for new advancements in AI technology. As the collaboration continues to evolve, the possibilities for AI development could reach unprecedented levels.

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MONAI medical imaging AI cloud service introduced by NVIDIA

MONAI medical imaging AI cloud service introduced by NVIDIA

NVIDIA has recently taken a bold step in the world of healthcare technology with the introduction of its MONAI Medical Imaging AI Cloud Service. This innovative service is set to make a big impact on how artificial intelligence (AI) models for medical imaging are developed, bringing new levels of efficiency and precision to the table. For those grappling with the complexities of medical imaging and the management of large datasets, NVIDIA’s latest offering could be a game-changer.

At the heart of the MONAI framework, a collaborative project with King’s College London, are cloud APIs that NVIDIA unveiled at the RSNA annual meeting. These APIs leverage the power of cloud computing to simplify the intricate processes involved in medical imaging. Imagine being able to manage the overwhelming flow of medical data with ease. NVIDIA’s MONAI cloud service provides powerful tools for annotation and handling large datasets, which is crucial in a field where data is not just abundant but also highly sensitive and complex.

MONAI medical imaging AI

The journey from the conception of an AI model to its deployment is often filled with obstacles. However, NVIDIA’s service is designed to accelerate this process. The integration of MONAI APIs with NVIDIA DGX Cloud and platforms like Flywheel is a testament to the service’s capability to speed up the development of healthcare AI models.

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NVIDIA’s reach with the MONAI cloud service is further extended through partnerships with companies like RedBrick AI and Dataiku. These partnerships aim to incorporate the MONAI cloud APIs into their solutions, thus enhancing the service’s impact.

One of the standout features of the service is VISTA-3D, which allows for interactive annotation. This feature encourages ongoing learning and the improvement of AI models, ensuring that they are always improving with new data inputs. Another significant feature is Auto3DSeg, which simplifies the 3D segmentation process by automating the tuning of hyperparameters and model selection. This automation is a major step forward, reducing the time and expertise required to fine-tune AI models for complex medical imaging tasks.

NVIDIA researchers have demonstrated the effectiveness of these tools in medical imaging competitions at the MICCAI conference. The message is clear: the MONAI cloud service is not only a valuable research tool but also a means to cut down the costs associated with developing AI models for radiology and disease investigation.

The adoption of NVIDIA’s MONAI cloud APIs by medical imaging solution providers and MLOps platforms signals a shift towards a more streamlined delivery of AI insights. This is crucial for providers who want to fully utilize the potential of AI in medical imaging.

NVIDIA’s MONAI Medical Imaging AI Cloud Service stands out as a key player in the healthcare industry. It offers a comprehensive suite of tools and features that simplify the creation and implementation of AI models in medical imaging. By choosing this service, you’re not just adopting cutting-edge technology; you’re also contributing to a future where medical diagnostics are more accurate, efficient, and widely available.

Image Credit : NVIDIA

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New NVIDIA Ethernet AI networking platform soon available

New NVIDIA Ethernet networking platform for AI soon available

NVIDIA has announce the imminent availability of its new Spectrum-X Ethernet networking solution, a technology poised to significantly boost AI system communication. This leap forward in networking performance is not just a standalone achievement; it’s part of a strategic alliance with industry giants Dell Technologies, Hewlett Packard Enterprise (HPE), and Lenovo. This collaboration ensures that Spectrum-X will be a core component of their server offerings, empowering enterprises to tackle the increasing demands of generative AI workloads with newfound efficiency.

AI applications are becoming more complex and data-intensive, requiring robust communication systems that can keep up. NVIDIA’s Spectrum-X is engineered to meet these challenges head-on, delivering a 1.6 times increase in networking performance over traditional Ethernet solutions. This enhancement is more than just a number—it’s the key to unlocking faster and more reliable AI communication, which is essential for the success of AI-driven projects.

The partnership between NVIDIA and the server manufacturers is a strategic move that goes beyond just improving performance. It’s about creating a unified system that leverages the full potential of each component. The forthcoming server systems will integrate Spectrum-X with NVIDIA’s advanced Tensor Core GPUs, AI Enterprise software, and AI Workbench software, creating an ecosystem that’s perfectly attuned to the needs of AI research and development.

Spectrum-X Ethernet AI networking

Leaders from NVIDIA, Dell, HPE, and Lenovo have all emphasized the significance of this joint effort. They recognize that the future of generative AI hinges on the seamless integration of accelerated networking and computing power. By combining these technologies, they are setting new standards for AI applications, from natural language processing to complex data analysis.

At the heart of Spectrum-X lies the Spectrum-4 Ethernet switch, a groundbreaking piece of technology that’s the first of its kind—a 51Tb/sec Ethernet switch designed with AI in mind. Its role is to reduce network congestion and streamline data flow, allowing AI systems to function with exceptional efficiency.

The Spectrum-4’s capabilities are further enhanced by the BlueField-3 SuperNIC network accelerator. These accelerators are not just about speed; they also provide secure, multi-tenant environments that are essential for modern data centers. In today’s world, where cloud computing and as-a-service models dominate, the need for security and isolation is paramount. The BlueField-3 SuperNICs are engineered to meet these critical requirements.

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Networks  designed for artificial intelligence

NVIDIA’s acceleration software suite, which includes development kits and the DOCA software framework, complements the hardware. These tools are designed to maximize the platform’s performance, giving developers the ability to harness the full power of the hardware. For those involved in AI model development, NVIDIA’s AI Enterprise and AI Workbench offer a set of indispensable resources. These tools are crucial for creating and scaling AI models, providing a foundation for innovation and progress.

The NVIDIA Israel-1 supercomputer, which runs on Spectrum-X, exemplifies the potential of this technology. It serves as a reference architecture for future AI systems, showcasing what can be achieved when these advanced technologies are integrated in a complementary fashion. The new systems that incorporate NVIDIA’s complete AI stack are expected to hit the market in the first quarter of the next year. This gives you ample time to plan and prepare for the integration of these sophisticated systems into your business operations.

As you consider the next steps for your organization’s AI capabilities, NVIDIA’s Spectrum-X Ethernet networking, combined with the server solutions from Dell, HPE, and Lenovo, represents a pivotal moment. With these cutting-edge tools at your disposal, you are well-positioned to tackle the most demanding AI workloads with confidence and skill. This strategic move by NVIDIA and its partners is not just about keeping pace with the evolution of AI—it’s about setting the pace, ensuring that enterprises like yours are always one step ahead.

Source: NVIDIA

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Dropbox partners with NVIDIA for generative AI for its customers

Dropbox partners with NVIDIA for generative AI for its customers 2023

Dropbox is looking to take its cloud storage service to a new level. Imagine cloud storage that doesn’t just hold your files but also intelligently organizes them, predicts your needs, and streamlines your workflow. This is the vision behind the recent collaboration between Dropbox and NVIDIA, two giants in their respective fields coming together to redefine how we interact with our digital content. By harnessing the power of advanced artificial intelligence, this partnership is set to enhance the way we manage our digital lives, making it more intuitive, efficient, and secure.

Dropbox, a leader in cloud storage and management, has embarked on a strategic alliance with NVIDIA, a titan in the world of AI and accelerated computing. This collaboration aims to infuse Dropbox’s cloud services with cutting-edge AI capabilities, designed to improve productivity and refine the way we handle our digital tasks. The integration of NVIDIA’s AI Foundation Models and AI Enterprise software into Dropbox’s ecosystem promises to deliver a smarter cloud experience that goes beyond simple storage solutions.

Dropbox Generative AI

The partnership introduces innovative AI-driven features such as Dropbox Dash and Dropbox AI. These tools are engineered to help declutter your digital workspace and assist in prioritizing tasks with ease. Imagine an AI that learns your habits and preferences, creating a Dropbox experience that feels like it was made just for you. This is the promise of the Dropbox-NVIDIA collaboration, where customized AI applications will enhance your file search capabilities, allowing you to find what you need quickly. Additionally, generative AI tools will intelligently categorize your content, streamlining your workflow to maximize efficiency.

The collaboration between Dropbox and NVIDIA is not just about adding new features; it’s about revolutionizing the way we manage our workflow. The integration of NVIDIA’s accelerated computing means that these AI-driven features will be fast, responsive, and highly effective. This is particularly important for knowledge workers who face challenges in managing their digital content and daily tasks. With these new tools, users can expect a significant improvement in their engagement with cloud content and task management.

Security and privacy

In the era of AI, security and privacy are more important than ever. Dropbox recognizes the critical nature of these issues and is committed to ensuring that the innovative features developed with NVIDIA are backed by robust security and privacy protocols. As these AI enhancements are rolled out, users can trust that their content will be managed intelligently and protected with the highest level of care.

Dropbox’s dedication to integrating AI into its services is not new, but the partnership with NVIDIA marks a significant leap forward. The company remains focused on delivering solutions that save time and enhance efficiency for its users. With NVIDIA’s comprehensive suite of AI tools, Dropbox is set to expand its AI capabilities, offering a cloud service that is not only smarter but also more attuned to the individual needs of its users.

The partnership between Dropbox and NVIDIA is paving the way for a new chapter in cloud services. By combining the best in AI technology, this partnership is poised to provide an exceptional digital experience. As these innovative features roll out, users can look forward to a more organized, efficient, and secure way of navigating their digital world. The future of cloud storage is not just about space; it’s about intelligence, and with Dropbox and NVIDIA at the helm, that future is bright and brimming with possibilities.

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NVIDIA and IQM Quantum Computers

NVIDIA and IQM Quantum Computers

The quantum computing field is on the cusp of a significant transformation, thanks to a pioneering partnership between IQM Quantum Computers and NVIDIA. This collaboration aims to advance the development of hybrid quantum applications, leveraging the capabilities of NVIDIA CUDA Quantum. This open-source platform is specifically designed to streamline the integration and programming of quantum processing units (QPUs), marking a new chapter in quantum computing.

This partnership is a significant leap forward in the quantum computing field. IQM, a leader in providing cutting-edge computing systems that utilize quantum bits, is known for its innovative approach to quantum computing. NVIDIA, on the other hand, is a global leader in GPU supercomputing and machine learning, making it an excellent partner for IQM in this ambitious project.

The primary goal of this collaboration is to advance the development of hybrid quantum applications using NVIDIA CUDA Quantum. CUDA Quantum is an open-source platform that simplifies the integration and programming of QPUs. This platform is set to revolutionize the development and application of quantum computing, enabling users of IQM’s QPUs across various industries and research institutions to develop the next generation of hybrid quantum-classical applications.

Quantum Computers

Another key objective of this partnership is to speed up the development and application of quantum computing. By leveraging the capabilities of CUDA Quantum, the partnership aims to accelerate the evolution and application of quantum computing across various fields. This will not only stimulate innovation but also pave the way for potential scientific and industrial breakthroughs.

Prominent institutions such as the CSC – IT Centre for Science and the VTT Technical Research Centre of Finland are already planning to use CUDA Quantum on VTT’s 5-qubit quantum computer. This quantum computer, a joint venture between IQM and VTT, demonstrates the potential of quantum computing innovation. Other articles we have written that you may find of interest on the subject :

Looking ahead, IQM is dedicated to making the integration of quantum and classical systems more accessible to experts. The company is focusing on quantum-accelerated supercomputing, a concept that combines the power of traditional supercomputing with the unique capabilities of quantum computing. This could have significant implications across various sectors, including cybersecurity and drug and chemical research.

The partnership between IQM Quantum Computers and NVIDIA is set to reshape the quantum computing landscape. By driving the development of hybrid quantum applications through NVIDIA CUDA Quantum, this collaboration is poised to accelerate the evolution and application of quantum computing, laying the groundwork for future innovations and breakthroughs. With leading institutions already planning to use CUDA Quantum, and a future focus on quantum-accelerated supercomputing, the potential of this collaboration is truly exciting.

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Gaudi 2 Intel’s new AI weapon against NVIDIA

Gaudi 2 Intels new AI weapon against NVIDIA

The recent release of the MLPerf training v3.1 benchmark results by MLCommons has brought Intel’s Gaudi 2 accelerators and 4th Gen Intel Xeon Scalable processors into focus. These results highlight a significant improvement in AI training performance, with Intel’s Gaudi 2 showing a 2x performance increase when using the FP8 data type on the v3.1 training GPT-3 benchmark. This notable performance boost has drawn attention to the potential of Intel’s hardware in the AI industry.

Intel’s Gaudi 2 accelerators and 4th Gen Intel Xeon Scalable processors, equipped with Intel Advanced Matrix Extensions (Intel AMX), are specifically designed to meet the growing demands of AI computing. The Gaudi 2 has emerged as a strong competitor to NVIDIA’s H100, offering significant price-performance benefits that make it an appealing choice for those in the AI industry.

Intel Gaudi 2

The 4th Gen Intel Xeon Scalable processors, as versatile CPUs, have shown strong performance in the MLPerf benchmarks. Intel remains the only CPU vendor to submit MLPerf results, emphasizing its commitment to competitive AI solutions and its ambition to stay at the forefront of AI hardware development.

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The Role of FP8 Software in the Performance Leap

The use of the FP8 data type has been crucial in the performance leap of Intel’s Gaudi 2. This data type, along with software updates and optimizations, has enabled the Gaudi 2 to cut the time-to-train by more than half compared to the June MLPerf benchmark. This significant reduction in training time showcases the efficiency and power of Intel’s hardware.

Understanding AI Models and Benchmarking

The MLPerf training v3.1 benchmark results were obtained from a range of AI models, including the Stable Diffusion multi-modal model, RESNet50, RetinaNet, BERT, and DLRM dcnv2. These models, in various hardware setups, were thoroughly tested to assess their performance. The results of these tests offer valuable insights into the performance of different hardware setups and their impact on AI model performance.

Intel’s Commitment to AI

With ongoing software enhancements and the potential of data types like FP8, Intel expects further progress in AI performance results in future MLPerf benchmarks. The company’s steadfast commitment to AI hardware and software development is evident in its consistent benchmark submissions and the impressive performance of its products. Intel’s dedication to advancing AI technology is clear, and the company is set to continue making significant progress in this field.

The MLPerf training v3.1 benchmark results have emphasized the impressive performance of Intel’s Gaudi 2 accelerators and 4th Gen Intel Xeon Scalable processors. The use of the FP8 data type and software optimizations have played a significant role in this performance leap, positioning Intel as a strong player in the AI hardware market. These results underscore Intel’s commitment to delivering high-performance AI solutions and its ability to compete effectively in the rapidly evolving AI hardware landscape.

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NVIDIA shatters records, training AI models in under 4 Minutes

NVIDIA sets new AI training records

NVIDIA’s AI platform has once again demonstrated its capabilities by setting new records in the latest MLPerf industry benchmarks, a well-regarded measure for AI training and high-performance computing. The AI supercomputer, NVIDIA Eos, powered by a whopping 10,752 NVIDIA H100 Tensor Core GPUs and NVIDIA Quantum-2 InfiniBand networking, completed a training benchmark based on a GPT-3 model in a record-breaking 3.9 minutes. This significant improvement from the previous record demonstrates the potential for faster training times, which can reduce costs, save energy, and speed up product development, making it a game-changer in the industry.

These latest results were achieved by using the highest number of accelerators ever used in an MLPerf benchmark. This achievement underscores NVIDIA’s ability to meet the unique challenges of generative AI for the world’s largest data centers. Eos and Microsoft Azure used a full-stack platform of innovations in accelerators, systems, and software to achieve these groundbreaking results, showcasing the power of collaboration and technological advancement.

Training AI models

In this round, NVIDIA set several new records, further solidifying its position as a leader in the field. In addition to making significant advances in generative AI, the H100 GPUs were 1.6x faster than the previous round’s training recommender models. NVIDIA was the only company to run all MLPerf tests, further demonstrating its commitment to pushing the boundaries of AI technology.

six new performance record set by NVIDIA

The NVIDIA AI platform was used in submissions this round by eleven systems makers, including industry heavyweights such as ASUS, Dell Technologies, Fujitsu, GIGABYTE, Lenovo, QCT, and Supermicro. This widespread use of NVIDIA’s technology is a clear indication of its robustness, reliability, and acceptance in the industry, demonstrating its potential to revolutionize AI technology.

NVIDIA AI platform

In the MLPerf HPC, H100 GPUs delivered up to twice the performance of NVIDIA A100 Tensor Core GPUs. This performance boost was particularly noticeable when the H100 GPUs trained OpenFold, a model that predicts the 3D structure of a protein, in just 7.5 minutes, showcasing the power and efficiency of NVIDIA’s technology.

Several partners, including Dell Technologies, Clemson University, Texas Advanced Computing Center, Lawrence Berkeley National Laboratory, and Hewlett Packard Enterprise (HPE), made submissions on the NVIDIA AI platform in this round. This collaboration between NVIDIA and these organizations demonstrates the platform’s versatility and applicability across various sectors, highlighting its potential to transform industries.

MLPerf benchmarks

MLPerf benchmarks have received wide support from both industry and academia, with organizations such as Amazon, Arm, Baidu, Google, Harvard, HPE, Intel, Lenovo, Meta, Microsoft, NVIDIA, Stanford University, and the University of Toronto backing them. All the software NVIDIA used is available from the MLPerf repository, ensuring transparency and accessibility for all interested parties, further promoting the democratization of AI technology.

NVIDIA’s AI platform continues to set new standards in AI training and high-performance computing, as evidenced by its latest achievements in the MLPerf industry benchmarks. The platform’s ability to reduce costs, save energy, and speed up product development, coupled with its widespread adoption by system makers and partners, underscores its value and potential in advancing AI technology. This continued success is a testament to NVIDIA’s commitment to pushing the boundaries of AI technology and its potential to revolutionize industries.

Image Credit :  NVIDIA

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50+ New NVIDIA GeForce NOW games arriving this month

50 New NVIDIA GeForce NOW games arriving this month

NVIDIA has announced that it will be adding 54 new games to its GeForce NOW game streaming service expanding the library of available titles to even greater heights. One of the most notable additions to the GeForce NOW platform is Virtex Stadium, an innovative online virtual stadium designed for esports enthusiasts. This unique platform offers a dynamic and immersive experience for fans, transforming the way they engage with esports events.

Virtex Stadium is set to host the highly anticipated League of Legends world championship finals. This event, taking place on various dates throughout November, will allow fans to watch live competitions, interact with friends, and personalize avatars, all within the virtual stadium environment. The integration of Virtex Stadium into the GeForce NOW platform facilitates seamless access for members, eliminating the need for a new login and offering the option to link their Twitch accounts for chat and emote functions.

NVIDIA GeForce NOW games November 2023

In addition to Virtex Stadium, GeForce NOW’s November update also includes Apex Legends: Ignite, the latest season of the popular battle royale first-person shooter from Electronic Arts and Respawn Entertainment. This new season is now available to stream from the cloud on GeForce NOW, giving players the opportunity to experience the thrill of the game without the need for high-end hardware.

Apex Legends: Ignite introduces a plethora of new features and enhancements, including a new support Legend with shield-based abilities and a faster, more deadly Storm Point map. Furthermore, the update includes a new Battle Pass with a range of enticing rewards, adding an extra layer of excitement and incentive for players.

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Members can start their adventures now, along with 15 other games newly supported in the cloud this week:

  • Headbangers: Rhythm Royale (New release on Steam, Xbox and available on PC Game Pass, Oct. 31)
  • Jusant (New release on Steam, Xbox and available on PC Game Pass, Oct. 31)
  • RoboCop: Rogue City (New release on Steam, Nov. 2)
  • The Talos Principle 2 (New release on Steam, Nov. 2)
  • StrangerZ (New release on Steam, Nov. 3)
  • Curse of the Dead Gods (Xbox, available on Microsoft Store)
  • Daymare 1994: Sandcastle (Steam)
  • ENDLESS Dungeon (Steam)
  • F1 Manager 2023 (Xbox, available on PC Game Pass)
  • Heretic’s Fork (Steam)
  • HOT WHEELS UNLEASHED 2 – Turbocharged (Epic Games Store)
  • Kingdoms Reborn (Steam)
  • Q.U.B.E. 2 (Epic Games Store)
  • Soulstice (Epic Games Store)
  • Virtex Stadium (Free)

Then check out the plentiful games for the rest of November:

  • The Invincible (New release on Steam, Nov 6.)
  • Roboquest (New release on Steam, Nov. 7)
  • Stronghold: Definitive Edition (New release on Steam, Nov. 7)
  • Dungeons 4 (New release on Steam, Xbox and available on PC Game Pass, Nov. 9)
  • Space Trash Scavenger (New release on Steam, Nov. 9)
  • Spirittea (New release on Steam, Xbox and available on PC Game Pass, Nov 13)
  • Naheulbeuk’s Dungeon Master (New release on Steam, Nov 15)
  • Last Train Home (New release on Steam, Nov. 28)
  • Gangs of Sherwood (New release on Steam, Nov. 30)
  • Airport CEO (Steam)
  • Arcana of Paradise —The Tower (Steam)
  • Blazing Sails: Pirate Battle Royale (Epic Games Store)
  • Breathedge (Xbox, available on Microsoft Store)
  • Bridge Constructor: The Walking Dead (Xbox, available on Microsoft Store)
  • Bus Simulator 21 (Xbox, available on Microsoft Store)
  • Farming Simulator 19 (Xbox, available on Microsoft Store)
  • GoNNER (Xbox, available on Microsoft Store)
  • GoNNER2 (Xbox, available on Microsoft Store)
  • Hearts of Iron IV (Xbox, available on Microsoft Store)
  • Hexarchy (Steam)
  • I Am Future (Epic Games Store)
  • Imagine Earth (Xbox, available on Microsoft Store)
  • Jurassic World Evolution 2 (Xbox, available on PC Game Pass)
  • Land of the Vikings (Steam)
  • Onimusha: Warlords (Steam)
  • Overcooked! 2 (Xbox, available on Microsoft Store)
  • Saints Row IV (Xbox, available on Microsoft Store)
  • Settlement Survival (Steam)
  • SHENZHEN I/O (Xbox, available on Microsoft Store)
  • SOULVARS (Steam)
  • The Surge 2 (Xbox, available on Microsoft Store)
  • Thymesia (Xbox, available on Microsoft Store)
  • Trailmakers (Xbox, available on PC Game Pass)
  • Tropico 6 (Xbox, available on Microsoft Store)
  • Wartales (Xbox, available on PC Game Pass)
  • The Wonderful One: After School Hero (Steam)
  • Warhammer Age of Sigmar: Realms of Ruin (Steam)
  • West of Dead (Xbox, available on Microsoft Store)
  • Wolfenstein: The New Order (Xbox, available on PC Game Pass)
  • Wolfenstein: The Old Blood (Steam, Epic Games Store, Xbox and available on PC Game Pass)

The addition of these 54 new games, including Virtex Stadium and Apex Legends: Ignite, to NVIDIA’s GeForce NOW in November marks a significant advancement in the platform’s offerings. By continually expanding its game library and incorporating innovative features like virtual esports stadiums, GeForce NOW is setting new standards in the cloud gaming industry. It’s clear that GeForce NOW is committed to providing its members with a diverse and immersive gaming experience, and these latest additions are a testament to that commitment.

The expansion of GeForce NOW’s game library, along with the integration of innovative platforms like Virtex Stadium, is a significant step forward in the cloud gaming industry. As NVIDIA continues to add new titles and features to its GeForce NOW service, it’s clear that the future of cloud gaming is bright, with limitless opportunities for growth and innovation.

Outstanding October
On top of the 60 games announced in October, an additional 48 joined the cloud last month, including several from this week’s additions, Curse of the Dead Gods, ENDLESS Dungeon, Farming Simulator 19, Hearts of Iron IV, Kingdoms Reborn, RoboCop: Rogue City, StrangerZ, The Talos Principle 2, Thymesia, Tropico 6 and Virtex Stadium:

  • AirportSim (New release on Steam, Oct. 19)
  • Battle Chasers: Nightwar (Xbox, available on Microsoft Store)
  • Black Skylands (Xbox, available on Microsoft Store)
  • Blair Witch (Xbox, available on Microsoft Store)
  • Call of the Sea (Xbox, available on Microsoft Store
  • Chicory: A Colorful Tale (Xbox and available on PC Game Pass)
  • Cricket 22 (Xbox and available on PC Game Pass)
  • Dead by Daylight (Xbox and available on PC Game Pass)
  • Deceive Inc. (Epic Games Store)
  • Dishonored (Steam)
  • Dishonored: Death of the Outsider (Steam, Epic Games Store, Xbox and available on PC Game Pass)
  • Dishonored Definitive Edition (Epic Games Store, Xbox and available on PC Game Pass)
  • Dishonored 2 (Steam, Epic Games Store, Xbox and available on PC Game Pass)
  • Dune: Spice Wars (Xbox and available on PC Game Pass)
  • Eternal Threads (New release on Epic Games Store, Oct. 19)
  • Everspace 2 (Xbox and available on PC Game Pass)
  • EXAPUNKS (Xbox and available on PC Game Pass)
  • From Space (New release on Xbox, available on PC Game Pass, Oct. 12)
  • Ghostrunner 2 (New release on Steam, Oct. 26)
  • Ghostwire: Tokyo (Steam, Epic Games Store, Xbox and available on PC Game Pass)
  • Golf With Your Friends (Xbox, available on PC Game Pass)
  • Gungrave G.O.R.E (Xbox and available on PC Game Pass)
  • The Gunk (Xbox and available on PC Game Pass)
  • Hotel: A Resort Simulator (New release on Steam, Oct. 12)
  • Kill It With Fire (Xbox and available on PC Game Pass)
  • Railway Empire 2 (Xbox and available on PC Game Pass)
  • Rubber Bandits (Xbox, available on PC Game Pass)Saints Row IV (Xbox, available on Microsoft Store)
  • Saltsea Chronicles (New release on Steam, Oct. 12)
  • Soulstice (Epic Games Store)
  • State of Decay 2: Juggernaut Edition (Steam, Epic Games Store, Xbox and available on PC Game Pass)
  • Supraland Six Inches Under (Epic Games Store)
  • Techtonica (Xbox and available on PC Game Pass)
  • Teenage Mutant Ninja Turtles: Shredder’s Revenge (Xbox and available on PC Game Pass)
  • Torchlight III (Xbox and available on PC Game Pass)
  • Totally Accurate Battle Simulator (Xbox and available on PC Game Pass)
  • Tribe: Primitive Builder (New release on Steam, Oct. 12)
  • Trine 5: A Clockwork Conspiracy (Epic Games Store)

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NVIDIA Omniverse receives DLSS 3.5 with ray reconstruction

DLSS 3.5 With Ray Reconstruction Now Available in NVIDIA Omniverse

The recent release of NVIDIA DLSS 3.5 update with Ray Reconstruction for NVIDIA Omniverse has sparked a significant evolution in the realm of 3D tool and app development. This update, which is also supported by the forthcoming NVIDIA Studio Driver release, has been eagerly anticipated by the community due to its promise of improved graphical fidelity and upscaling for native videos.

The DLSS 3.5 update not only enhances ray-traced image quality on GeForce RTX GPUs but also replaces hand-tuned denoisers with an AI network trained by an NVIDIA supercomputer. This feature represents a significant leap forward in the field, as it provides a more sophisticated and nuanced approach to image quality enhancement.

NVIDIA Omniverse

In addition to DLSS 3.5, the NVIDIA Studio Driver release will also introduce RTX Video Super Resolution (VSR). This new feature promises to further enhance the capabilities of NVIDIA’s groundbreaking technology, offering users the opportunity to experience even more stunning graphics and videos.

One of the most exciting aspects of these updates is their support for GeForce RTX 20 Series GPUs. This inclusion in the 1.5 update opens up these advanced features to a broader range of users, making cutting-edge graphics technology more accessible than ever before.

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DLSS 3.5 with ray reconstruction

The potential of these updates is perhaps best illustrated by the Halloween-themed projection mapping project undertaken by NVIDIA Creative Director, Sabour Amirazodi. Utilizing NVIDIA GPU-accelerated MadMapper software and a DSLR camera, Amirazodi created a virtual scene on his house for his annual “Haunted Sanctuary” installation.

The use of NVIDIA technologies in this project demonstrates how GPU acceleration can streamline workflow and enhance creative output. Amirazodi used GPU acceleration to animate and rig characters, resulting in a visually stunning and immersive experience. This project was not only a technical triumph but also a community effort, with Amirazodi stating that the hard work was worth it for the joy it brought to his neighborhood.

In addition to facilitating such innovative projects, NVIDIA is also encouraging creators to submit harvest and fall-themed pieces for the #SeasonalArtChallenge through November. This initiative showcases the versatility of NVIDIA’s technology, demonstrating its applicability across a wide range of creative endeavors.

The release of NVIDIA DLSS 3.5 update with Ray Reconstruction for NVIDIA Omniverse represents a significant advancement in the field of 3D tool and app development. With its improved graphical fidelity, support for GeForce RTX 20 Series GPUs, and the introduction of RTX Video Super Resolution, this update promises to revolutionize the way we experience and interact with digital content. From projection mapping projects to creative challenges, the possibilities are endless, and we can’t wait to see what the future holds.

Source & Image Credit : NVIDIA Omniverse

Filed Under: Technology News, Top News





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