There are worlds where performance matters. For example HPC world: faster software means less wait time for the scientists. Embedded world: faster software means we can use cheaper silicon to build our product. Game world: faster software means that our game will run on slower CPUs, thus making our game more interesting to people with […]
Parallelware Analyzer
Parallelware Analyzer 0.17 released
We are pleased to announce the availability of Parallelware Analyzer 0.17 which includes many new exciting features. New vectorization support introduces detection of opportunities for vectorization and the generation of compiler-specific and portable directives. A lot of effort has also been put into improving usability through a redesigned reporting that reflects the function and loop […]
A touch of parallelism: example of NPB CG Benchmark
Our ultimate goal at Appentra is to create a software suite that will help users achieve the peak performance of their software. One of the ways to do it is with a touch of parallelism. This post will talk about the NPB CG benchmark, a popular benchmark for comparing supercomputers, developed by NASA. We will […]
Parallelware Analyzer 0.16 released
We are pleased to announce the availability of Parallelware Analyzer 0.16. This release features a redesigned pwloops tool and new checks to improve the detection of data races and GPU data movement issues: Redesign of pwloops to better match the parallelization workflow: first, make sure that the code is analyzable; second, see what computation patterns […]
Parallelware Analyzer 0.15 released
We are excited to announce the availability Parallelware Analyzer 0.15. This release has the following new features: Memory access patterns reporting. Now pwloops provides information not only about computational parallel patterns but also about memory access patterns. You can find more information about the patterns in our knowledge base. Use OpenMP teams to offload to […]
Interprocedural analysis across source code files with Parallelware Analyzer
Programs are rarely built from a single source code file. Normally, code is organized into several source files, reaching hundreds or even thousands of files for large programs. Static code analysis tools work by analyzing the source code files. When a function defined in a source file calls another function defined in a different source […]
Using CMake’s compilation database with Parallelware Analyzer
When building a program, seldom do we only invoke the compiler passing a source file and an output binary name. In most cases, we must supply several compiler flags such as include paths or macro definitions. A program is usually built by compiling different source files where each may require different compiler flags. One of […]
Parallelware Analyzer 0.14 now available in the Early Access Program
We are happy to announce the availability of Parallelware Analyzer 0.14. This release has a significant number of new features: Linux, Windows and MacOS versions: Parallelware Analyzer was available for Linux x86 and Power architectures supporting C/C++ and Fortran; now it is also available for Windows and MacOS supporting C/C++. Data race free analysis: pwcheck […]
Appentra raises €1.8M co-led by Armilar Venture Partners and K Fund for its Parallelware Analyzer software
Today we are excited to announce that Appentra has raised €1.8M in a round led by Armilar Venture Partners and K Fund, also joined by Caixa Capital Risc, Xesgalicia and Unirisco, the investors that had already trusted us in the very early stages of the company. During the last months we have been working hand […]
Parallelware Analyzer NPB Quickstart
Index What is Parallelware Analyzer?– Where to start?– Useful options common to all toolsQuickstart with NAS Parallel BenchmarksUsing a configuration file Early Access Program is now open! Enter the program to have access to all versions of Parallelware Analyzer and support until the official release. What is Parallelware Analyzer? Parallelware Analyzer is a suite of […]