This is a package for inference of protein activity from gene expression data. It includes the VIPER and msVIPER algorithms

This package is used for the detection of differentially expressed genes (DEGs) from the comparison of two biological conditions (treated vs. untreated, diseased vs. normal, mutant vs. wild-type) among different levels of gene expression (transcriptome ,translatome, proteome), using several statistical methods: Rank Product, Translational Efficiency, t-test, Limma, ANOTA, DESeq, edgeR. It also provides the possibility to plot the results with scatterplots, histograms, MA plots, standard deviation (SD) plots, coefficient of variation (CV) plots.

Kokkos Core implements a programming model in C++ for writing performance portable applications targeting all major HPC platforms. For that purpose it provides abstractions for both parallel execution of code and data management. Kokkos is designed to target complex node architectures with N-level memory hierarchies and multiple types of execution resources.

Kokkos Core implements a programming model in C++ for writing performance portable applications targeting all major HPC platforms. For that purpose it provides abstractions for both parallel execution of code and data management. Kokkos is designed to target complex node architectures with N-level memory hierarchies and multiple types of execution resources.

Kokkos Core implements a programming model in C++ for writing performance portable applications targeting all major HPC platforms. For that purpose it provides abstractions for both parallel execution of code and data management. Kokkos is designed to target complex node architectures with N-level memory hierarchies and multiple types of execution resources.

Kokkos Core implements a programming model in C++ for writing performance portable applications targeting all major HPC platforms. For that purpose it provides abstractions for both parallel execution of code and data management. Kokkos is designed to target complex node architectures with N-level memory hierarchies and multiple types of execution resources.

Kokkos Core implements a programming model in C++ for writing performance portable applications targeting all major HPC platforms. For that purpose it provides abstractions for both parallel execution of code and data management. Kokkos is designed to target complex node architectures with N-level memory hierarchies and multiple types of execution resources.

Kokkos Core implements a programming model in C++ for writing performance portable applications targeting all major HPC platforms. For that purpose it provides abstractions for both parallel execution of code and data management. Kokkos is designed to target complex node architectures with N-level memory hierarchies and multiple types of execution resources.

Kokkos Core implements a programming model in C++ for writing performance portable applications targeting all major HPC platforms. For that purpose it provides abstractions for both parallel execution of code and data management. Kokkos is designed to target complex node architectures with N-level memory hierarchies and multiple types of execution resources.

This package provides several cubic spline interpolation methods of H. Akima for irregular and regular gridded data are available through this package, both for the bivariate case and univariate case. Linear interpolation of irregular gridded data is also covered. A bilinear interpolator for regular grids was also added for comparison with the bicubic interpolator on regular grids.

The rfacts package is an R interface to the Fixed and Adaptive Clinical Trial Simulator FACTS. It programmatically invokes FACTS to run clinical trial simulations. It aggregates simulation output data into tidy data frames. These capabilities provide end-to-end automation for large-scale simulation pipelines, and they enhance computational reproducibility.

This package provides the CUDA compiler and the CUDA run-time support libraries for NVIDIA GPUs, all of which are proprietary.

This package provides a system-wide performance analysis tool designed to visualize an application’s algorithms, identify the largest opportunities to optimize, and tune to scale efficiently across any quantity or size of CPUs and GPUs,from large servers to small systems-on-a-chip.

This package provides a set of APIs which can be used at runtime to combine multiple CUDA objects into one CUDA fat binary (fatbin). The APIs accept inputs in multiple formats, either device cubins, PTX, or LTO-IR. The output is a fatbin that can be loaded by cuModuleLoadData of the CUDA Driver API. The functionality in this library is similar to the fatbinary offline tool in the CUDA toolkit, with the following advantages:

• Support for runtime fatbin creation.

• The clients get fine grain control over the input process.

• Supports direct input from memory, rather than requiring inputs be written to files.

This package provides a set of GPU-accelerated basic linear algebra subroutines used for handling sparse matrices that perform significantly faster than CPU-only alternatives. Depending on the specific operation, the library targets matrices with sparsity ratios in the range between 70%-99.9%.

CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance matrix-matrix multiplication (GEMM) and related computations at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS and cuDNN.

CUTLASS decomposes these ``moving parts'' into reusable, modular software components abstracted by C++ template classes. Primitives for different levels of a conceptual parallelization hierarchy can be specialized and tuned via custom tiling sizes, data types, and other algorithmic policy. The resulting flexibility simplifies their use as building blocks within custom kernels and applications.

This package provides the CUDA compiler and the CUDA run-time support libraries for NVIDIA GPUs, all of which are proprietary.

OpenCL (Open Computing Language) is a multi-vendor open standard for general-purpose parallel programming of heterogeneous systems that include CPUs, GPUs and other processors. This package provides the API to use OpenCL on NVIDIA GPUs.

This package provides a set of APIs which can be used at runtime to link together GPU devide code. It supports Link Time Optimization.

This package enables the creation of profiling and tracing tools that target CUDA applications and give insight into the CPU and GPU behavior of CUDA applications. It provides the following APIs:

• the Activity API,

• the Callback API,

• the Event API,

• the Metric API,

• the Profiling API,

• the PC Sampling API,

• the Checkpoint API.

This package decodes (demangles) low-level identifiers that have been mangled by CUDA C++ into user readable names. For every input alphanumeric word, the output of cu++filt is either the demangled name if the name decodes to a CUDA C++ name, or the original name itself.

This package provides the NVIDIA tool for debugging CUDA applications running. CUDA-GDB is an extension to GDB, the GNU Project debugger. The tool provides developers with a mechanism for debugging CUDA applications running on actual hardware. This enables developers to debug applications without the potential variations introduced by simulation and emulation environments.

This package provides the CUDA compiler and the CUDA run-time support libraries for NVIDIA GPUs, all of which are proprietary.

This package provides the CUDA compiler and the CUDA run-time support libraries for NVIDIA GPUs, all of which are proprietary.