HPC Compiler Company PathScale Seeks Life Raft

By Tiffany Trader

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. A letter from the company with a listing of assets is included at the end of the article.

PathScale represents one of handful of compiler technologies that are designed for high performance computing, and it is one the last independent HPC compiler companies. In an interview with HPCwire, PathScale Chief Technology Officer and owner Christopher Bergström attributes the company’s financial insolvency to its heavy involvement in Intel alternative architectures.

“Unfortunately in recent years, we bet big on ARMv8 and the partner ecosystem and the hardware has been extremely disappointing,” said Bergström. “Once partners saw how low their hardware performed on HPC workloads they decided to pull back on their investment in HPC software.”

Due to confidentiality agreements, he’s limited to speaking in generalities but argues that the currently available ARMv8 processors deliver very weak performance for HPC workloads.

“ARM is possibly aware of this issue and as a result has introduced SVE (Scalable Vector Extensions),” Bergström told us. “Unfortunately, they focused more on the portability side of vectorization and the jury is still out if they can deliver competitive performance. SVE’s flexible design and freedom to change vector width on the fly will possibly impact the ability to write code tuned specifically for a target processor. In addition, design of the hardware architecture blocks software optimizations that are very common and potentially critical for HPC. And based on the publicly available roadmaps, the floating point to power ratio is not where it needs to be for HPC workloads in order to effectively compete against Intel or GPUs.”

Before coming to these conclusions, PathScale had a statement of work contract with Cavium to help support optimizing compilers for their ThunderX processors. When that funding was pulled, PathScale also lost their ability to gain and support customers for ARMv8. They looked for funders, and had conversations with stakeholders in the private and public sphere, but the money just wasn’t available.

“Show me a company in the HPC space wanting to invest,” said Bergström, “They’re not investing in compiler technology.”

ARM, which was scooped up by Japanese company SoftBank in September 2016 for $31 billion, may be the exception, but according to Bergström the PathScale technology, while it significantly leverages LLVM, doesn’t perfectly align with what they need.

Bergström brokered the deal with Cray that resurrected PathScale from the ashes of SiCortex in 2009 (more on this below) and he’s proud of what he and his team have accomplished over the last seven years. “We love compilers, we love the technology. We want to continue developing this stuff. The team is rock solid, we’re like family. We live eat and breathe compilers, but we’re not on a sustainable business path and we need a bailout or help refocusing. We need people who understand that these kind of technologies add value and LLVM by itself isn’t a panacea.”

Addison Snell, CEO of HPC analyst firm Intersect360 Research, shared some additional perspective on the market dynamics at play for independent tools vendors. “In the Beowulf era, clusters were all mostly the same, so what little differentiation there was came from things like development environments and job management software,” he said. “Independent middleware companies of all types flourished. Now we’re trending back toward an era of architectural specialization. Users are shopping for architectures more than they’re shopping for which compiler to use for a given architecture, and acquisitions have locked up some of the previously dominant players. Vendors’ solutions will have their own integrated stacks. Free open-source versions might still exist, but there will be less room for independent middleware players.”

PathScale has a winding history that dates back to 2001 with the founding of Key Research by Lawrence Livermore alum Tom McWilliams. The company was riding the commodity cluster wave, developing clustered Linux server solutions based on a low-cost 64-bit design. In 2003, contemporaneous with the rising popularity of AMD Opteron processors, Key Research rebranded as PathScale and expanded its product line to include high-performance computing adapters and 64-bit compilers.

PathScale would then pass through a number of corporate hands. In 2006, QLogic acquired PathScale, primarily to gain access to its InfiniBand interconnect technology. The following year, the compiler assets were sold to SiCortex, which sought a solution for its MIPS-based HPC systems.

When SiCortex closed its doors in 2009, Cray bought the PathScale assets and revived the company. Under an arrangement struck with Cray, PathScale would go forward as an independent technology group with an option to buy. In March 2012, PathScale CTO Christopher Bergström acquired all assets and became the sole owner of PathScale Inc.

The PathScale toolchain currently generates code for the latest Intel processors, AMD64, AMD GPUs, Power8, ARMv8, and NVIDIA GPUs in combination with both Power8 and x86.

In a message to the community, Pathscale writes:

We are evaluating all options to overcome this difficult time, including refocusing to provide training and code porting services instead of purely offering compiler licenses and optimization services. Our team deeply understands parallel programming and whether you have crazy C++ or ancient Fortran, we can likely help get it running on GPUs (NVIDIA or AMD) or vectorization targets (like Xeon Phi).

All PathScale engineers would love to continue to work on the compiler as an independent company, but we need the community to help us. We need people who believe in our technical roadmap. We need people who understand the future exascale computing software stack will likely be complex, but that complexity and advanced optimizations will make it easier for end users. At the same time we must be realistic and without immediate assistance start accepting any reasonable offer on the assets as a whole or piece by piece.

Our assets include:

  • PathScale website, trademarks and branding

  • C, C++ and Fortran compilers

  • Complete GPGPU and many-core runtime which supports OMP4 and OpenACC and is portable across multiple architectures (NVIDIA GPU, ARMv8, Power8+NVIDIA and AMD GPU)

  • Significant modifications to CLANG and LLVM to enable support for OpenACC and OpenMP and parallel programming models.

  • Complete engineering team with expertise working on CLANG and LLVM and MIPSPro.

  • Advertising credits with popular websites ($30,000)

A purchase or funding from crowdsourcing or other community event will keep a highly optimizing OpenMP and OpenACC C/C++ and Fortran compiler toolchain plus experienced development team in operation. Succinctly, PathScale preserves architectural diversity and opens the door for competition with a performant compiler for interesting architectures with OpenMP and OpenACC parallelization.

If interested please contact [email protected].


Editor’s note: HPCwire has reached out to Cavium and ARM and we will update the article with any responses we receive.

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