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| LIKWID | |
|---|---|
| Name | LIKWID |
| Operating system | Linux |
| Genre | Performance tools |
| License | GPL |
LIKWID
LIKWID is a lightweight set of performance tools for Linux for measuring and controlling hardware performance on x86 processors. It targets developers, system administrators, and researchers working with Intel Corporation and AMD microarchitectures, providing utilities for clock control, thread affinity, and hardware counter access. The suite complements profiling frameworks and observability stacks used in high-performance computing environments such as clusters managed by SLURM Workload Manager and installations at institutions like Lawrence Berkeley National Laboratory.
LIKWID addresses common needs in performance engineering on x86-64 systems by exposing processor features through simple command-line tools. It interacts with interfaces provided by Linux kernel subsystems and leverages model-specific registers present in Intel Core and AMD Ryzen families. The project situates itself among tools like perf (Linux) and PAPI while emphasizing minimal dependencies and ease of use for users of libraries such as OpenMP and MPI (Message Passing Interface). Its design reflects practices from academic groups at universities and national laboratories collaborating on performance reproducibility.
The suite comprises multiple utilities that provide distinct functions: - A thread and process affinity manager comparable to features in numactl and taskset, enabling pinning for OpenMP threads and POSIX threads. - Access to hardware performance counters akin to PAPI functionality, allowing events from Intel VTune-style counters and AMD μProf-compatible metrics. - Clock and power control mechanisms similar to functionality in cpufrequtils and Intel SpeedStep controls, enabling frequency governors tuning relevant to Green500 and energy-aware benchmarking. - Topology and cache information reporting, integrating CPU topology concepts used in Linux kernel scheduler research and system topology tools like hwloc. Each component is implemented as a small standalone binary that interfaces with system resources commonly used in supercomputing centers such as Oak Ridge National Laboratory and Argonne National Laboratory.
LIKWID's architecture centers on direct access to model-specific registers and Linux perf infrastructure through compact C code and minimal external libraries. It uses syscall interfaces maintained by Linux kernel contributors and relies on CPUID mechanisms standardized in Intel 64 and AMD64 architectures. The toolchain is intended to be built with compilers like GCC and Clang (compiler), and integrates with build systems used in research software engineering such as GNU Make and CMake. The implementation patterns mirror low-level utilities developed at organizations like Red Hat and research groups at Technische Universität München.
Common usage scenarios include binding threads for reproducible experiments in scientific software stacks like PETSc and Trilinos (software), measuring cache misses for codes ported to CUDA-accelerated nodes managed by OpenMPI, and exploring frequency effects on algorithms used in LAMMPS or GROMACS. Typical commands resemble affinity pinning examples found in documentation for OpenMP and MPI: - Pinning worker threads when launching job scripts under SLURM Workload Manager on clusters like those at National Energy Research Scientific Computing Center. - Sampling hardware events for matrix multiplication kernels used in studies at Massachusetts Institute of Technology and ETH Zurich. - Adjusting CPU frequency governors prior to running benchmarks common in SPEC CPU suites and HPC benchmarks from Top500 submissions. Examples are concise and map to common workflows in research labs at University of California, Berkeley and Stanford University.
Benchmarks using LIKWID typically appear in publications on multicore scalability, cache optimization, and energy-efficiency research published in venues like SC (conference) and IEEE transactions. Results often compare measurements from LIKWID with outputs from perf (Linux), Intel VTune, and PAPI to validate counter accuracy and overhead. Use cases include roofline model construction for codes developed at NERSC and performance counter-based analyses in papers from EPFL and University of Illinois Urbana–Champaign. LIKWID's low runtime overhead and deterministic affinity behavior make it suitable for microbenchmarking and large-scale studies reported at conferences such as ISC High Performance.
The project is maintained by contributors from academic and laboratory environments, with development practices influenced by open-source projects hosted on platforms like GitHub and coordinated through issue trackers and mailing lists similar to those used by Linux kernel development. Community contributions often come from researchers at institutions like Technical University of Munich and Friedrich Schiller University Jena, and users report integrations with cluster management systems maintained by teams at CERN and Deutsches Klimarechenzentrum. Documentation and discussion occur in forums frequented by developers of OpenMP runtimes and maintainers of HPC toolchains.
LIKWID is used in academia, national laboratories, and industry for performance tuning of scientific applications such as LAMMPS, GROMACS, NAMD (software), OpenFOAM, and numerical libraries like BLAS and LAPACK. Operators at supercomputing centers including Oak Ridge National Laboratory and Lawrence Livermore National Laboratory deploy LIKWID for node-level diagnostics and tuning during procurement and acceptance testing for systems listed in Top500. Research groups studying energy-aware algorithms reference LIKWID in papers alongside tools from Intel and AMD ecosystems when reporting reproducible performance and power results.
Category:Performance tools