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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 the CUDA compiler and the CUDA run-time support libraries for NVIDIA GPUs, all of which are proprietary.
This package accepts CUDA C++ source code in character string form and creates handles that can be used to obtain the CUDA PTX, for further instrumentation with the CUDA Toolkit. It allows to shrink compilation overhead and simplify application deployment.
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.
This package provides an interface for generating PTX code from both binary and text NVVM IR inputs.
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.
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 GPU-accelerated library of primitives for deep neural networks, with highly tuned implementations for standard routines such as forward and backward convolution, attention, matmul, pooling, and normalization.
This binary extracts information from standalone cubin files and presents them in human readable format. The output of nvdisasm includes CUDA assembly code for each kernel, listing of ELF data sections and other CUDA specific sections. Output style and options are controlled through nvdisasm command-line options. nvdisasm also does control flow analysis to annotate jump/branch targets and makes the output easier to read.
This package provides a minimal low-level profiling API for CUDA.
This package provides tooling to configure the NVSwitch memory fabrics to form one memory fabric among all participating GPUs, and monitors the NVLinks that support the fabric. See docs for more information.
This package provides a <bits/floatn.h> header to override that of glibc and disable float128 support. This is required allow the use of nvcc with CUDA 8.0 and glibc 2.26+. Otherwise, nvcc fails like this:
/gnu/store/…-glibc-2.26.105-g0890d5379c/include/bits/floatn.h(61): error: invalid argument to attribute "__mode__" /gnu/store/…-glibc-2.26.105-g0890d5379c/include/bits/floatn.h(73): error: identifier "__float128" is undefined
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.
This package provides the proprietary cuTENSOR library for NVIDIA GPUs.
This package provides a cross-platform API for annotating source code to provide contextual information to developer tools.
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.
This package provides a set of APIs which can be used at runtime to link together GPU devide code. It supports Link Time Optimization.
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 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.