NVIDIA Unveils Tesla K80 Dual-GPU Accelerator

November 17, 2014

NEW ORLEANS, La., Nov. 17 — NVIDIA today unveiled a new addition to the NVIDIA Tesla Accelerated Computing Platform: the Tesla K80 dual-GPU accelerator, the world’s highest performance accelerator designed for a wide range of machine learning, data analytics, scientific, and high performance computing (HPC) applications.

The Tesla K80 dual-GPU is the new flagship offering of the Tesla Accelerated Computing Platform, the leading platform for accelerating data analytics and scientific computing. It combines the world’s fastest GPU accelerators, the widely used CUDA parallel computing model, and a comprehensive ecosystem of software developers, software vendors, and datacenter system OEMs.

The Tesla K80 dual-GPU accelerator delivers nearly two times higher performance and double the memory bandwidth of its predecessor, the Tesla K40 GPU accelerator. With ten times higher performance than today’s fastest CPU, it outperforms CPUs and competing accelerators on hundreds of complex analytics and large, computationally intensive scientific computing applications.

Users can unlock the untapped performance of a broad range of applications with the accelerator’s enhanced version of NVIDIA GPU Boost technology (PDF), which dynamically converts power headroom into the optimal performance boost for each individual application.

Industry-Leading Performance for Science, Data Analytics, Machine Learning

The Tesla K80 dual-GPU accelerator was designed with the most difficult computational challenges in mind, ranging from astrophysics, genomics and quantum chemistry to data analytics. It is also optimized for advanced deep learning tasks, one of the fastest growing segments of the machine learning field.

“NVIDIA GPUs have become the de facto computing platform for the deep learning community,” said Yann LeCun, director of AI Research at Facebook, and Silver Professor of Computer Science & Neural Science at New York University. “Because the accuracy of deep learning systems improves as the models and datasets get larger, we always look for the fastest hardware we can find. The Tesla K80 accelerator, with its dual-GPU architecture and large memory, gives us more teraflops and more GB than ever before from a single server, allowing us to make faster progress in deep learning.”

The Tesla K80 delivers up to 8.74 teraflops single-precision and up to 2.91 teraflops double-precision peak floating point performance, and10 times higher performance than today’s fastest CPUs on leading science and engineering applications, such as AMBER, GROMACS, Quantum Espresso and LSMS.

“The Tesla K80 dual-GPU accelerators are up to 10 times faster than CPUs when enabling scientific breakthroughs in some of our key applications, and provide a low energy footprint,” said Wolfgang Nagel, director of the Center for Information Services and HPC at Technische Universität Dresden in Germany. “Our researchers use the available GPU resources on the Taurus supercomputer extensively to enable a more refined cancer therapy, understand cells by watching them live, and study asteroids as part of ESA’s Rosetta mission.”

Key features of the Tesla K80 dual-GPU accelerator include:

  • Two GPUs per board – Doubles throughput of applications designed to take advantage of multiple GPUs.
  • 24GB of ultra-fast GDDR5 memory – 12GB of memory per GPU, 2x more memory than Tesla K40 GPU, allows users to process 2x larger datasets.
  • 480GB/s memory bandwidth – Increased data throughput allows data scientists to crunch though petabytes of information in half the time compared to the Tesla K10 accelerator. Optimized for energy exploration, video and image processing, and data analytics applications.
  • 4,992 CUDA parallel processing cores – Accelerates applications by up to 10x compared to using a CPU alone.
  • Dynamic NVIDIA GPU Boost Technology – Dynamically scales GPU clocks based on the characteristics of individual applications for maximum performance.
  • Dynamic Parallelism – Enables GPU threads to dynamically spawn new threads, enabling users to quickly and easily crunch through adaptive and dynamic data structures.

The Tesla K80 accelerates the broadest range of scientific, engineering, commercial and enterprise HPC and data center applications — more than 280 in all. The complete catalog of GPU-accelerated applications (PDF) is available as a free download.

More information about the Tesla K80 dual-GPU accelerator is available at NVIDIA booth 1727 at SC14, Nov. 17-20, and on the NVIDIA high performance computing website.

Availability

Shipping today, the NVIDIA Tesla K80 dual-GPU accelerator will be available from a variety of server manufacturers, including ASUS, Bull, Cirrascale, Cray, Dell, Gigabyte, HP, Inspur, Penguin, Quanta, Sugon, Supermicro and Tyan, as well as from NVIDIA reseller partners.

About the Tesla Accelerated Computing Platform

The Tesla Accelerated Computing Platform is designed from the ground up for power-efficient, high performance computing, computational science, supercomputing, enterprise, complex data analytics and machine learning applications. It delivers dramatically higher performance and energy efficiency than a CPU-only approach. The platform deeply integrates the world’s fastest GPU accelerators, development tools, high-speed communication technology, a supported ecosystem and NVIDIA CUDA, the world’s most pervasive parallel computing model.

Source: NVIDIA

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

EU Spending €28 Million on AI Upgrade to Leonardo Supercomputer

September 19, 2024

The seventh fastest supercomputer in the world, Leonardo, is getting a major upgrade to take on AI workloads. The EuroHPC JU is spending €28 million to upgrade Leonardo to include new GPUs, CPUs and "high-bandwidth mem Read more…

Google’s DataGemma Tackles AI Hallucination

September 18, 2024

The rapid evolution of large language models (LLMs) has fueled significant advancement in AI, enabling these systems to analyze text, generate summaries, suggest ideas, and even draft code. However, despite these impress Read more…

Quantum and AI: Navigating the Resource Challenge

September 18, 2024

Rapid advancements in quantum computing are bringing a new era of technological possibilities. However, as quantum technology progresses, there are growing concerns about the availability of resources—a challenge remin Read more…

Intel’s Falcon Shores Future Looks Bleak as It Concedes AI Training to GPU Rivals

September 17, 2024

Intel's Falcon Shores future looks bleak as it concedes AI training to GPU rivals On Monday, Intel sent a letter to employees detailing its comeback plan after an abysmal second-quarter earnings report with critics calli Read more…

AI Helps Researchers Discover Catalyst for Green Hydrogen Production

September 16, 2024

Researchers from the University of Toronto have used AI to generate a “recipe” for an exciting new catalyst needed to produce green hydrogen fuel. As the effects of climate change begin to become more apparent in our Read more…

The Three Laws of Robotics and the Future

September 14, 2024

Isaac Asimov's Three Laws of Robotics have captivated imaginations for decades, providing a blueprint for ethical AI long before it became a reality. First introduced in his 1942 short story "Runaround" from the "I, R Read more…

Google’s DataGemma Tackles AI Hallucination

September 18, 2024

The rapid evolution of large language models (LLMs) has fueled significant advancement in AI, enabling these systems to analyze text, generate summaries, sugges Read more…

Quantum and AI: Navigating the Resource Challenge

September 18, 2024

Rapid advancements in quantum computing are bringing a new era of technological possibilities. However, as quantum technology progresses, there are growing conc Read more…

Shutterstock_2176157037

Intel’s Falcon Shores Future Looks Bleak as It Concedes AI Training to GPU Rivals

September 17, 2024

Intel's Falcon Shores future looks bleak as it concedes AI training to GPU rivals On Monday, Intel sent a letter to employees detailing its comeback plan after Read more…

The Three Laws of Robotics and the Future

September 14, 2024

Isaac Asimov's Three Laws of Robotics have captivated imaginations for decades, providing a blueprint for ethical AI long before it became a reality. First i Read more…

GenAI: It’s Not the GPUs, It’s the Storage

September 12, 2024

A recent news release from Data storage company WEKA and S&P Global Market Intelligence unveiled the findings of their second annual Global Trends in AI rep Read more…

Shutterstock 793611091

Argonne’s HPC/AI User Forum Wrap Up

September 11, 2024

As fans of this publication will already know, AI is everywhere. We hear about it in the news, at work, and in our daily lives. It’s such a revolutionary tech Read more…

Quantum Software Specialist Q-CTRL Inks Deals with IBM, Rigetti, Oxford, and Diraq

September 10, 2024

Q-CTRL, the Australia-based start-up focusing on quantum infrastructure software, today announced that its performance-management software, Fire Opal, will be n Read more…

AWS’s High-performance Computing Unit Has a New Boss

September 10, 2024

Amazon Web Services (AWS) has a new leader to run its high-performance computing GTM operations. Thierry Pellegrino, who is well-known in the HPC community, has Read more…

Everyone Except Nvidia Forms Ultra Accelerator Link (UALink) Consortium

May 30, 2024

Consider the GPU. An island of SIMD greatness that makes light work of matrix math. Originally designed to rapidly paint dots on a computer monitor, it was then Read more…

AMD Clears Up Messy GPU Roadmap, Upgrades Chips Annually

June 3, 2024

In the world of AI, there's a desperate search for an alternative to Nvidia's GPUs, and AMD is stepping up to the plate. AMD detailed its updated GPU roadmap, w Read more…

Nvidia Shipped 3.76 Million Data-center GPUs in 2023, According to Study

June 10, 2024

Nvidia had an explosive 2023 in data-center GPU shipments, which totaled roughly 3.76 million units, according to a study conducted by semiconductor analyst fir Read more…

Shutterstock_1687123447

Nvidia Economics: Make $5-$7 for Every $1 Spent on GPUs

June 30, 2024

Nvidia is saying that companies could make $5 to $7 for every $1 invested in GPUs over a four-year period. Customers are investing billions in new Nvidia hardwa Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Shutterstock 1024337068

Researchers Benchmark Nvidia’s GH200 Supercomputing Chips

September 4, 2024

Nvidia is putting its GH200 chips in European supercomputers, and researchers are getting their hands on those systems and releasing research papers with perfor Read more…

IonQ Plots Path to Commercial (Quantum) Advantage

July 2, 2024

IonQ, the trapped ion quantum computing specialist, delivered a progress report last week firming up 2024/25 product goals and reviewing its technology roadmap. Read more…

Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's l Read more…

Leading Solution Providers

Contributors

Intel’s Next-gen Falcon Shores Coming Out in Late 2025 

April 30, 2024

It's a long wait for customers hanging on for Intel's next-generation GPU, Falcon Shores, which will be released in late 2025.  "Then we have a rich, a very Read more…

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators and Atos' financial turmoil have the HPC market worried. If Atos goes under, HPE will be the only major option for building large-scale systems. Read more…

xAI Colossus: The Elon Project

September 5, 2024

Elon Musk's xAI cluster, named Colossus (possibly after the 1970 movie about a massive computer that does not end well), has been brought online. Musk recently Read more…

Department of Justice Begins Antitrust Probe into Nvidia

August 9, 2024

After months of skyrocketing stock prices and unhinged optimism, Nvidia has run into a few snags – a  design flaw in one of its new chips and an antitrust pr Read more…

MLPerf Training 4.0 – Nvidia Still King; Power and LLM Fine Tuning Added

June 12, 2024

There are really two stories packaged in the most recent MLPerf  Training 4.0 results, released today. The first, of course, is the results. Nvidia (currently Read more…

Spelunking the HPC and AI GPU Software Stacks

June 21, 2024

As AI continues to reach into every domain of life, the question remains as to what kind of software these tools will run on. The choice in software stacks – Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Shutterstock 1886124835

Researchers Say Memory Bandwidth and NVLink Speeds in Hopper Not So Simple

July 15, 2024

Researchers measured the real-world bandwidth of Nvidia's Grace Hopper superchip, with the chip-to-chip interconnect results falling well short of theoretical c Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire