Blaze is an open-source, high-performance C++ math library for dense and sparse arithmetic. With its state-of-the-art Smart Expression Template implementation Blaze combines the elegance and ease of use of a domain-specific language with HPC-grade performance, making it one of the most intuitive and fastest C++ math libraries available.

The Blaze library offers:

• high performance through the integration of BLAS libraries and manually tuned HPC math kernels;

• vectorization by SSE, SSE2, SSE3, SSSE3, SSE4, AVX, AVX2, AVX-512, FMA, SVML, SLEEF, and XSIMD;

• parallel execution by OpenMP, HPX, C++11 threads and Boost threads;

• an intuitive and easy to use API of a domain specific language;

• unified arithmetic with dense and sparse vectors and matrices;

• thoroughly tested matrix and vector arithmetic;

• completely portable, high quality C++ source code.

Chameleon is a dense linear algebra solver relying on sequential task-based algorithms where sub-tasks of the overall algorithms are submitted to a run-time system. Such a system is a layer between the application and the hardware which handles the scheduling and the effective execution of tasks on the processing units. A run-time system such as StarPU is able to manage automatically data transfers between not shared memory area (CPUs-GPUs, distributed nodes).

PyLops is an open-source Python library focused on providing a backend-agnostic, idiomatic, matrix-free library of linear operators and related computations. It is inspired by the iconic MATLAB Spot – A Linear-Operator Toolbox project.

qr_mumps is a software package for the solution of sparse, linear systems on multicore computers based on the QR factorization of the input matrix. Therefore, it is suited to solving sparse least-squares problems and to computing the minimum-norm solution of sparse,underdetermined problems. It can obviously be used for solving square problems in which case the stability provided by the use of orthogonal transformations comes at the cost of a higher operation count with respect to solvers based on, e.g., the LU factorization. qr_mumps supports real and complex, single or double precision arithmetic. This is an experimental version of the package for distributed memory.

Composyx is a linear algebra C++ library focused on composability. Its purpose is to allow the user to express a large pannel of algorithms using a high-level interface to range from laptop prototypes to many node supercomputer parallel computations.

This software’s goal is to propose a parallel algebraic strategy to decompose a sparse linear system Ax=b, enabling its resolution by a domain decomposition solver. Up to now, Paddle is implemented for the MaPHyS linear solver.

Ginkgo is a high-performance numerical linear algebra library for many-core systems, with a focus on solution of sparse linear systems.

Bazel is a build and test tool similar to Make, Maven, and Gradle. It uses a human-readable, high-level build language. Bazel supports projects in multiple languages and builds outputs for multiple platforms. Bazel supports large codebases across multiple repositories, and large numbers of users.

Bazel is a build and test tool similar to Make, Maven, and Gradle. It uses a human-readable, high-level build language. Bazel supports projects in multiple languages and builds outputs for multiple platforms. Bazel supports large codebases across multiple repositories, and large numbers of users.

Bazel is a build and test tool similar to Make, Maven, and Gradle. It uses a human-readable, high-level build language. Bazel supports projects in multiple languages and builds outputs for multiple platforms. Bazel supports large codebases across multiple repositories, and large numbers of users.

Bazel is a build and test tool similar to Make, Maven, and Gradle. It uses a human-readable, high-level build language. Bazel supports projects in multiple languages and builds outputs for multiple platforms. Bazel supports large codebases across multiple repositories, and large numbers of users.

mpiGraph is a MPI benchmark to generate network bandwidth images.

HPL is a software package that solves a (random) dense linear system in double precision (64 bits) arithmetic on distributed-memory computers. It can thus be regarded as a portable as well as freely available implementation of the High Performance Computing Linpack Benchmark.

GPCNeT is a benchmark suite that includes simulated network congestion, allowing the benchmarking of network performance in closer-to-real-conditions in HPC networks.

The benchmarks are derived from computational fluid dynamics (CFD) applications and consist of five kernels and three pseudo-applications in the original "pencil-and-paper" specification (NPB 1). The benchmark suite has been extended to include new benchmarks for unstructured adaptive meshes, parallel I/O, multi-zone applications, and computational grids. Problem sizes in NPB are predefined and indicated as different classes.

The benchmarks are derived from computational fluid dynamics (CFD) applications and consist of five kernels and three pseudo-applications in the original "pencil-and-paper" specification (NPB 1). The benchmark suite has been extended to include new benchmarks for unstructured adaptive meshes, parallel I/O, multi-zone applications, and computational grids. Problem sizes in NPB are predefined and indicated as different classes.

Create an interactive Shiny-based graphical user interface for exploring data stored in SummarizedExperiment objects, including row- and column-level metadata. The interface supports transmission of selections between plots and tables, code tracking, interactive tours, interactive or programmatic initialization, preservation of app state, and extensibility to new panel types via S4 classes. Special attention is given to single-cell data in a SingleCellExperiment object with visualization of dimensionality reduction results.

This is an R package which interfaces with the OME Bio-Formats Java library to allow reading of proprietary microscopy image data and metadata.

SHARC is a pipeline for somatic SV calling and filtering from tumor-only Nanopore sequencing data. It performs mapping, SV calling, SV filtering, random forest classification, blacklist filtering and SV prioritization, followed by automated primer design for PCR amplicons of 80-120 bp that are useful to track cancer ctDNA molecules in liquid biopsies.

The goal of NicheNet is to study intercellular communication from a computational perspective. NicheNet uses human or mouse gene expression data of interacting cells as input and combines this with a prior model that integrates existing knowledge on ligand-to-target signaling paths. This allows to predict ligand-receptor interactions that might drive gene expression changes in cells of interest.

This package provides an implementation of the CaVEMan program. It uses an expectation maximisation approach to calling single base substitutions in paired data. It is designed for use with a compute cluster. Most steps in the program make use of an index parameter. The split step is designed to divide the genome into chunks of adjustable size to optimise for runtime/memory usage requirements.