Volta Adds Charge to GPU Roadmap

By Nicole Hemsoth

March 21, 2013

When it comes to the future of GPU computing, NVIDIA CEO Jen-Hsun Huang said during this week’s GTC keynote that the emphasis will be on blending general computing, physics and simulation into one high performance yet energy-efficient package.

According to Huang, the next generation of both data- and compute-intensive apps will require higher performance to meet real-time demands. On the other end, this all has to happen within an energy consumption framework that doesn’t obliterate the ROI of spicing up a datacenter with GPU acceleration.

Outside of these higher-level focal points, other issues, including snappy access to high memory bandwidth, were cited as critical to growing the GPU user ranks. Memory and power will become even more relevant as data volume and velocity requirements expand into new application areas that are reliant on memory maximization without breaking the power consumption bank. These are among some of the identified “big data” problems NVIDIA is seeking to address for both its research and enterprise users.

While “Maxwell” is still sitting on the sidelines until later this year, Huang said the unified virtual memory approach extends Kepler’s forked focus on power, performance and programmability for the present. The newest addition to the GPU ranks is called “Volta,” which when released in the expected 2016 range, will take the three “P” aspects one step further by stepping up to a stacked memory approach.

In essence, with Volta, they’re removing the power hop of getting off the chip and onto DRAM – instead, as the name implies, they’re going to literally stack the DRAM onto the substrate, pierce through them from top to bottom to connect the stacked memories. While the notion of stacked memory isn’t necessarily new, it is still maturing – and NVIDIA sees serious potential.

The promise of Volta is two-fold – on the one hand, it will represent a big step toward practical stacked memory, something that former Cray wizard and current NVIDIA CTO on the Tesla side, Steve Scott, thinks is not yet ready for primetime. During our chat following the keynote, he said that while there are some noteworthy attempts at bringing stacked memory to market from companies like Micron, there are some serious engineering hurdles left to leap (packaging, capacities, degree of routing needed, etc.).

On the secondary side, anything that can be done to minimize one of the real costs of both performance and energy is data movement. Scott noted that Volta, and also Maxwell to a great degree, derive their energy efficiency by tightening up how far data travels. It’s not hard to see how stacking the package could enhance this efficiency focus – not to mention produce some rather stunning bandwidth.

While current generation GPUs’ bandwidth is higher than with a CPU, it’s still never quite at the level users will want. But NVIDIA claims that once Volta rolls out they’ll be able to boast 1 terabyte per second – the equivalent, as Huang described, of loading an entire Blueray into memory and running it through the chip in 1/50 of a second.

As Scott described, NVIDIA sees the need to “find ways to make more of our memory accesses – to work toward memory structures that take less energy to access.” As he noted, that’s where stacked memory comes in: “you can take 3D stacked memory technology and get much better bandwidth at much lower energy per bit to access memory from these 3D stacks than to go to main memory.” This idea is doubtlessly simple, he says, however the technology hasn’t even begun to round the bend to readiness.

There are still considerations to make in terms of tradeoffs. While latency isn’t much different in this projected new sibling to the NVIDIA GPU family, the on-package memory will be smaller, more expensive, but really high bandwidth and lower energy. It’s good that it’s high bandwidth and low energy but the smaller and more expensive part is tough. Scott says they’re looking to address that, but these are considerations for the coming decade.

Almost all HPC applications will be able to take advantage of a stacked memory offering, just as they can with cache today. As Scott described, “you still have your main memory where most of your data sits but you have some kernel that’s operating on some working set and you can usually block it so that you can put a chunk of data in the near memory and access it multiple times.” There are a few problems that won’t fit nicely in this paradigm, but these are already ones that have a hard time making top use of memory to begin with – a prime example is a graph problem since it lacks a great degree of locality.

The section where Huang talks about the roadmap and provides some visual details is below.

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!

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion XL — were added to the benchmark suite as MLPerf continues Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing power it brings to artificial intelligence.  Nvidia's DGX Read more…

Call for Participation in Workshop on Potential NSF CISE Quantum Initiative

March 26, 2024

Editor’s Note: Next month there will be a workshop to discuss what a quantum initiative led by NSF’s Computer, Information Science and Engineering (CISE) directorate could entail. The details are posted below in a Ca Read more…

Waseda U. Researchers Reports New Quantum Algorithm for Speeding Optimization

March 25, 2024

Optimization problems cover a wide range of applications and are often cited as good candidates for quantum computing. However, the execution time for constrained combinatorial optimization applications on quantum device Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at the network layer threatens to make bigger and brawnier pro Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HBM3E memory as well as the the ability to train 1 trillion pa Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

NVLink: Faster Interconnects and Switches to Help Relieve Data Bottlenecks

March 25, 2024

Nvidia’s new Blackwell architecture may have stolen the show this week at the GPU Technology Conference in San Jose, California. But an emerging bottleneck at Read more…

Who is David Blackwell?

March 22, 2024

During GTC24, co-founder and president of NVIDIA Jensen Huang unveiled the Blackwell GPU. This GPU itself is heavily optimized for AI work, boasting 192GB of HB Read more…

Nvidia Looks to Accelerate GenAI Adoption with NIM

March 19, 2024

Today at the GPU Technology Conference, Nvidia launched a new offering aimed at helping customers quickly deploy their generative AI applications in a secure, s Read more…

The Generative AI Future Is Now, Nvidia’s Huang Says

March 19, 2024

We are in the early days of a transformative shift in how business gets done thanks to the advent of generative AI, according to Nvidia CEO and cofounder Jensen Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. 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 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

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 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

Intel Won’t Have a Xeon Max Chip with New Emerald Rapids CPU

December 14, 2023

As expected, Intel officially announced its 5th generation Xeon server chips codenamed Emerald Rapids at an event in New York City, where the focus was really o Read more…

IBM Quantum Summit: Two New QPUs, Upgraded Qiskit, 10-year Roadmap and More

December 4, 2023

IBM kicks off its annual Quantum Summit today and will announce a broad range of advances including its much-anticipated 1121-qubit Condor QPU, a smaller 133-qu Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire