What Scalable Parallel Computing Lab at ETH Zurich (SPCL@ETH) does

The Scalable Parallel Computing Lab (SPCL) is an academic research group within the Department of Computer Science at ETH Zurich, established in 2017 and led by Torsten Hoefler. SPCL conducts research in all areas of scalable computing, organized around three primary research directions: scalable high-performance networking (novel topologies, routing, host interfaces for large-scale networks), parallel programming (advanced techniques and runtime environments), and performance (modeling, simulation, and optimization of large-scale parallel applications). The lab collaborates extensively with industry partners, other academic institutions, and HPC centers worldwide, and has produced notable contributions including the Slim Fly network topology, MPI standard contributions, and graph processing research.

Name

Scalable Parallel Computing Lab at ETH Zurich (SPCL@ETH)

Legal name

Scalable Parallel Computing Laboratory (SPCL) at ETH Zurich

Website

https://spcl.ethz.ch

Company type

Private

Operating status

Operating

Headcount range

1–10 employees

Short description

The Scalable Parallel Computing Lab (SPCL) at ETH Zurich is an academic research group led by Torsten Hoefler, conducting research in scalable networking, parallel programming, and performance modeling for high-performance computing, serving academia, HPC centers, and industry research partners.

Ownership category

akta.pro rank

GTM type

B2B

Offering type

Services

Cost components

Personnel, Technology or R&D, Operations, Infrastructure, Others

Marketing channels4 records

Core offering

SPCL is an academic research laboratory that performs research in all areas of scalable computing, with primary directions in Scalable High-Performance Networking, Parallel Programming, and Performance Modeling. Its outputs are research publications, open-source code, the SPCL_Bcast open online seminar series, and university-level teaching such as the Parallel Programming course at ETH Zurich. The lab does not commercialize products or services; it is funded through institutional support and external research grants.

Product overview

SPCL (Scalable Parallel Computing Laboratory) at ETH Zurich is an academic research laboratory, not a commercial product company. The lab's activities primarily consist of research projects, publications, and educational programs. SPCL_Bcast is an open online seminar series covering parallel computing and HPC topics. The lab also offers educational services through courses like Parallel Programming taught by Torsten Hoefler and Barbara Solenthaler.

Differentiator

Problem solved

Functional benefit

Brands

• SPCL_Bcast: An open, online seminar series covering topics around parallel and high-performance computing, scalable machine learning, and related areas.

Products and services

• SPCL_Bcast Open online seminar series covering a broad range of topics around parallel and high-performance computing, scalable machine learning, and related areas, offered freely to the research community.
• Parallel Programming Course Semester course taught at ETH Zurich covering parallel programming techniques, offered as part of the curriculum to ETH students.

Quantifiable outcome

• Over 500 publications at top HPC, ML, and systems venues (SC, ISCA, MICRO, NeurIPS, ICML, etc.)
• +2 more outcomes

Segments5 records

Ideal customer profiles4 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

Feature4 records

Recent moves5 records

Expansion highlights4 records

Regional players

• NERSC at Lawrence Berkeley National Laboratory: U.S. national HPC user facility focused on performance, applications, and scalable computing for scientific workloads. Comparable research focus on performance modeling and optimization but operates as a user facility rather than a free-standing research group.
• RWTH Aachen University - HPC Center: European academic HPC center with research in parallel programming, performance tools, and scalable systems. Comparable in scope and European academic footprint, though not a globally dominant brand.

Broad incumbents

• Argonne National Laboratory - Mathematics and Computer Science: U.S. Department of Energy lab with extensive HPC research including parallel programming, performance modeling, and exascale system software. Comparable research areas but with a broader mandate and larger scale than SPCL.
• Lawrence Livermore National Laboratory (LLNL) - HPC Division: U.S. national lab with one of the largest HPC research groups, covering programming models, performance, networking, and exascale systems. Comparable research portfolio but operating at significantly larger scale and with mission-driven (national security) focus.

Direct peers

• Max Planck Institute for Informatics (MPI-INF) - Computer Graphics and Parallel Computing: German academic research institute conducting systems, algorithms, and parallel computing research with strong publication output. Comparable in academic mission, publication quality, and European HPC ecosystem engagement.
• Barcelona Supercomputing Center (BSC): European HPC research center conducting parallel programming, runtime, and computer architecture research with strong industry and academic partnerships. Comparable in scale, research breadth, and exascale focus.
• Stanford Computer Science - HPC and Systems Group: Top-tier U.S. academic CS department with research in parallel systems, compilers, and computer architecture. Comparable in advancing scalable computing research and training influential systems researchers.
• Innovative Computing Laboratory, University of Tennessee: Academic HPC research lab focused on parallel programming, runtime systems, and performance optimization for large-scale systems, with deep MPI and benchmarking contributions. Highly comparable to SPCL in mission, scope, and industry collaboration model.
• Jülich Supercomputing Centre (JSC): German national supercomputing center with deep research in scalable parallel applications, programming models, and HPC architectures. Comparable in mission and academic/government collaboration profile.
• MIT CSAIL Parallel Computing Research: Leading U.S. academic research group conducting work in parallel computing, programming languages, and systems. Comparable in producing top-tier publications and training HPC talent.

Market position

Strengths4 records

Weaknesses4 records

Competitive moat5 records

Key risks4 records

Key highlights6 records

Customer concentration

• LinkedInlinkedin.com/company/spcl

Revenue estimate

Valuation estimate

Number of profiles

Profiles1 record

Funding overview

Funding rounds

Investors

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M&A

Investments

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Frequently asked questions about Scalable Parallel Computing Lab at ETH Zurich (SPCL@ETH)