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| ParaTools | |
|---|---|
| Name | ParaTools |
| Industry | Software performance engineering |
| Founded | 2001 |
| Headquarters | Cambridge, Massachusetts |
| Key people | Donald Becker, William Gropp, Katherine Yelick |
| Products | Tau, PerfSuite, ParaProfiler |
ParaTools
ParaTools is a software company specializing in performance analysis, profiling, and optimization of parallel and distributed applications. It provides tools and services used in high-performance computing, scientific computing, and enterprise data centers to analyze performance bottlenecks and guide optimization on systems that include supercomputers, clusters, and cloud platforms. The company’s offerings intersect with research communities, national laboratories, and commercial firms that rely on MPI, OpenMP, CUDA, and containerized deployments.
ParaTools traces its roots to performance engineering efforts in the early 2000s that built on contributions from researchers at organizations such as the National Center for Supercomputing Applications, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, and Sandia National Laboratories. The company was founded amid advancements in tools used by projects like MPI Forum implementations, OpenMP Architecture Review Board initiatives, and compiler toolchains from GNU Project and Intel Corporation. Its timeline is connected to developments in parallel runtime systems from groups associated with University of California, Berkeley, Massachusetts Institute of Technology, University of Illinois Urbana-Champaign, and University of Tennessee performance tools. Over time, ParaTools engaged with programs funded by agencies including the National Science Foundation, the Department of Energy, and the Defense Advanced Research Projects Agency.
ParaTools develops performance tools and consulting services that complement established products from vendors such as Cray Inc., IBM, Hewlett Packard Enterprise, NVIDIA, and AMD. Its flagship analysis suite supports workflows previously addressed by tools like TAU Performance System derivatives and integrates with runtime libraries from Open MPI, MPICH, Intel MPI Library, and NVIDIA CUDA Toolkit. Services include performance auditing for centers using systems from Fujitsu, HPE Cray, and cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform. The company supplies training and support aligned with initiatives at institutions such as Princeton University, Stanford University, California Institute of Technology, and Cornell University.
ParaTools’ methodology builds on instrumentation, sampling, and tracing techniques used in projects like PAPI (Performance API), LTTng, and DTrace, combined with analytics approaches pioneered in academic labs at University of Cambridge, EPFL, and ETH Zurich. Its toolchain interoperates with build systems and debuggers from GNU Compiler Collection, LLVM Project, GDB, and TotalView Technologies. Analysis workflows leverage visualization paradigms from software such as Paraview and VisIt, and performance counters conforming to standards advocated by Intel Corporation and AMD. The company applies reproducible benchmarking practices influenced by benchmarks like SPEC CPU and HPCG and integrates with continuous integration systems including Jenkins, GitLab CI/CD, and Travis CI.
ParaTools’ products are applied in domains that include computational fluid dynamics projects at centers like NASA Ames Research Center and European Centre for Medium-Range Weather Forecasts, molecular dynamics research at Argonne National Laboratory and Sandia National Laboratories, and seismic imaging efforts at firms such as Schlumberger and Halliburton. Other use cases include machine learning workloads optimized for frameworks like TensorFlow, PyTorch, and MXNet on accelerators from NVIDIA and AMD Instinct. ParaTools supports simulations for initiatives led by Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and computational chemistry efforts tied to Royal Society of Chemistry collaborations. Enterprise analytics customers include financial services firms that run workloads on platforms developed by Bloomberg L.P. and Goldman Sachs.
The company’s leadership has included figures with academic and industry backgrounds who have collaborated with researchers affiliated with University of California, Santa Barbara, University of Michigan, Georgia Institute of Technology, Rice University, and Duke University. Technical staff often hold prior affiliations with laboratories such as Argonne National Laboratory, Oak Ridge National Laboratory, and corporate engineering groups at Intel Corporation and NVIDIA. Governance and advisory relationships have intersected with nonprofit entities like The Linux Foundation and standards bodies such as the OpenMP Architecture Review Board and the MPI Forum.
ParaTools has partnered with supercomputing centers including National Energy Research Scientific Computing Center, Oak Ridge Leadership Computing Facility, and Texas Advanced Computing Center, and worked with vendors like Cray Inc., HPE, Dell Technologies, and Lenovo. Collaborative research projects involved universities such as University of Oxford, Imperial College London, University of Edinburgh, and University of Tokyo, as well as consortia including PRACE and XSEDE. The company has been involved in grant-funded initiatives with agencies like the European Research Council and national laboratories participating in programs run by the U.S. Department of Energy.
ParaTools and its technologies have been cited in contributions to conferences and workshops such as SC (conference), International Conference for High Performance Computing, Networking, Storage and Analysis, ACM/IEEE Supercomputing Conference, IEEE International Parallel and Distributed Processing Symposium, and publications in journals associated with ACM and IEEE. The company’s staff and tools have been acknowledged in award contexts related to work supported by the National Science Foundation and collaborative achievements recognized at events hosted by organizations like Argonne National Laboratory and Lawrence Berkeley National Laboratory.