PeakStream Dissolution Shines Spotlight on Stream Computing

By Michael Feldman

June 15, 2007

Last week's acquisition of PeakStream by Google is still reverberating in the tech world.  IT watchers have offered various explanations as to why the Internet giant bought a tiny company that develops stream computing technology for high performance, multicore processors.  I chimed in with my own speculations last week. Theories for the acquisition usually revolved around Google's use of multicore technology to expand their Internet empire. The company's scaled-out computing infrastructure will surely be dependent on multicore hardware, so why not own some technology that exploits that kind of architecture in a novel way?

But let's face it — even if Google uses the PeakStream stream computing technology to accelerate its own Web applications, it still seems a bit odd for a company that develops Internet software to be interested in owning a particular development platform. Then again, Google is an unusual IT company. Even though its main products are search engines, multimedia aggregators and web tools, Google also builds and maintains its own cyberinfrastructure. Rather than buying systems from cluster vendors, the company rolls its own from commodity x86 boards and Ethernet components (although of late it has become more secretive about this). So far this approach has worked out well for the Internet giant. It boasts one of the most efficient and robust distributed computing environments in the world. The inclusion of PeakStream may be just another manifestation of Google's inclination to control the means to its Internet ends.

However, a more logical buyer of a PeakStream's multicore programming platform would have been Microsoft. Now that's a company with a direct interest in multicore software technology. Essentially all of the processor  targets for Microsoft software are now multicore. And not only does Microsoft sell its own software development platforms, it also writes operating systems and applications. The hardware-agnostic PeakStream technology would appear to be a perfect fit for a software company that wants to incorporate multicore technology at every level of its offerings. The fact that Microsoft is now in the HPC business would have made a PeakStream acquisition that much more logical. If I were in a cynical mood, I might suggest that Google spirited away PeakStream to prevent Microsoft from getting it.

One thing is certain. The PeakStream acquisition focused some attention on their former rival, RapidMind Inc., a company that offers a very similar type of stream computing platform. RapidMind's product debuted in May, seven months after PeakStream delivered its first version. Ray DePaul, president and CEO of RapidMind, talked to me about his thoughts on the Google-PeakStream deal and what it might mean to his company.

Naturally, he was pleased that stream computing was getting some free publicity because of the acquisition. “This is a real validation of what's possible with this type of technology,” said DePaul. “Anyone who looks at Google as a threat, a mentor or a technology leader should be a little concerned that they just leapfrogged everyone yet again.”

But according to DePaul, RapidMind was less of a direct competitor with PeakStream than what has been portrayed in the press. He maintains that their customer base and plans for their product evolution is independent of what PeakStream was doing. Nevertheless, DePaul admitted that a handful of former PeakStream customers have already approached his company. Since RapidMind actually supports a broader array of target processors than PeakStream did, presumably the customer base can switch platforms fairly easily should they choose to do so.

DePaul maintains the real challenge for them was (and is) overcoming the resistance to using a high-level solution for performance-sensitive applications. Both PeakStream and RapidMind had to convince potential customers that their stream computing approach was the best way forward for multicore programming, not just because it was easier to use, but also because a systems approach could exploit more parallelism than a manual implementation. “Our main competitor is companies that think they can tackle the multithreaded game in the traditional way,” said DePaul. “The in-house do-it-yourselfer is what we have to sell against.”

RapidMind even encountered some of this resistance in their engagement with IBM, when working with the Cell processor team. But the IBMers had to be impressed when the RapidMind platform beat out the Cell programmers on a renderer application run on a Cell blade. In this case, the RapidMind-generated solution was able to double the performance compared to a hand-coded version. If RapidMind is able to maintain that kind of performance edge across an array of applications and processor targets, users should flock to the company's platform.

As far as becoming an acquisition target themselves, DePaul expressed that he has no interest in going down that path. His goal is to support as many platforms and applications as possible with the RapidMind offering. Currently over a thousand developers are using their product and a number of firms are looking into licensing the RapidMind technology.

Said DePaul: “I'm focused on building a company, not getting acquired by somebody in the Valley.”

—–

As always, comments about HPCwire are welcomed and encouraged. Write to me, Michael Feldman, at [email protected].

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