Faster development of parallel software ensuring best practices with Parallelware
Unlock the performance of modern multicore CPUs and GPUs through static code analysis tools specializing in parallelism.
Develop bug-free parallel code ensuring best practices for safety and performance.
Detect and prevent parallel bugs originated by data races and data movement issues, and get best-practice recommendations to develop faster software.
A new catalog of parallel programming
best practices and common errors
Ensure the quality of C/C++/Fortran parallel code according to best practices
Open catalog of defects and recommendations for parallel programming built in collaboration with experts in multicore and GPU programming to establish parallel programming best practices. Open set of curated example codes that clearly describe errors commonly seen in C/C++/Fortran parallel codes.
Enforce best practices in your parallel code with the Parallelware tools
Products based on the Parallelware static code analysis technology are the first tools supporting this innovative catalog by reporting race conditions, data movement issues and best-practice recommendations to create efficient and bug-free parallel code.
Capabilities of Parallelware tools
Parallelware tools provide an innovative solution for the development of C/C++/Fortran parallel code targeting multicore CPUs and GPUs. Its new static code analysis specializing in parallelism helps to accelerate the software run-time by reducing development effort through detection and generation of bug-free parallel code.
Accelerate the software runtime through code parallelization
Discover opportunities for parallelization in your code
Quickly design and implement parallel code for CPU/GPU using OpenMP/OpenACC.
Detect and fix defects such as data movement issues in parallel code using OpenMP/OpenACC.
Verify data-race free parallel code using OpenMP/OpenACC.
Enforce parallel programming best practice recommendations in order to prepare the code for parallelization or optimize its performance.
A static code analyzer specialized in parallelism
Parallelware Analyzer helps developers create fast, correct parallel code in C/C++/Fortran, reportingproviding them with feedback in the form of objective and measurable metrics and. seamlessly integrating into their development workflow and CI/CD tool.
Learn parallel programming faster and at your own pace
Learn parallelization concepts and techniques guided by parallel patterns used in real software. Use our integrated learning environment to experiment with different technologies for parallel programming. Make expert decisions for the development of multicore and GPU-accelerated software.
4 tips to avoid race conditions on GPUs
The 4 tips presented leverage parallel programming best practices, enabling to write parallel code as good as that written by experts in parallel programming for GPUs. They cover two typical data movement issues, one typical data race, and one recommendation to prevent introducing bugs in the parallel code inadvertently.