Cusparse example code. The figure shows CuPy speedup over NumPy.

Cusparse example code 141) and added some code to realize it. … CUDA Library Samples. import numpy as np import cupy as cp Just like Numpy, CuPy also have a ndarray class cupy. * Block-SpMM code example[](#block-spmm_code_example) --------------------------------------------------- For this new storage format, perform similar steps as with CSR and COO `cusparseSpMM`. White paper describing how to use the cuSPARSE and cuBLAS libraries to achieve a 2x speedup over CPU in the incomplete-LU and Cholesky preconditioned iterative methods. 2. When running on an AMD machine it will call rocSPARSE. 0. In addition to including the header file, you need to link to the library. The cuSPARSE API assumes that input and output data reside in GPU (device) memory, unless it is explicitly indicated otherwise by the string DevHostPtr in a function parameter's name (for example, the parameter A small example program for benchmarking cuSPARSE's csrmv routine with real-world data, against a randomly initialised vector. The cuSPARSE API assumes that input and output data reside in GPU (device) memory, unless it is explicitly indicated otherwise by the string DevHostPtr in a function parameter’s name. In other words, if a program uses cuSPARSE, it should continue to compile and work correctly with newer versions of cuSPARSE without source code changes. The general format of a CSR sparse matrix representation is documented in many places, including the CUSPARSE manual. I can get dense solver to give correct answers but the sparse solver does not so I must be doing something wrong. GraphBLAS does not strictly rely on standard linear algebra but on its small extensions Oct 2, 2025 · Contents The contents of the programming guide to the CUDA model and interface. Most operations perform well on a GPU using CuPy out of the box. CuPy utilizes CUDA Toolkit libraries including cuBLAS, cuRAND, cuSOLVER, cuSPARSE, cuFFT, cuDNN and NCCL to make full use of the GPU architecture. c, for example, in the windows file manager). I suspect this makes it impossible to compile with CUDA Fortran. In order to improve performance I want to replace cusparseSpMM from cuSparse with cusparseLtMatmul from cuSpareLt. Apr 12, 2023 · Thank you! I got a follow-up question. Jun 21, 2023 · I notice that in cusparse, there is cusparseXcscsort. CUDA Library Samples. Please visit cuSPARSE Library Samples - cusparseAxpby for a code example. 0 License. Download scientific diagram | cuSPARSE SpMV/SpMM performance and upperbound: Nvidia Pascal P100 GPU Fig. We first introduce an overview of the workflow by showing the main steps to set up the computation. Jul 12, 2025 · Importing - In the following code, cp is an abbreviation of cupy, as np is numpy as is customarily done. If you want to solve general system then please check cuDSS, cuDSS_doc and example. Test configuration for a BiCGStab implementation in Fortran using CUDA cuSparse routines This repos contains a set of files for testing implementations of a BiCGStab solver written in fortran and using CUDA cuSparse routines; the repo was created in order to ask for help on StackOverflow while providing source code. Sep 29, 2015 · 2 You can convert a dense matrix to sparse with code you write yourself. Dec 21, 2024 · gpu cublas nvidia nvml cudnn auto-generate cufft cuda-driver cusolver code-generate curand cusparse nvrtc cublaslt nvtx nvjpeg cuda-hook cuda-hijack cudart nvblas Updated on Dec 11, 2023 C I'm a beginner in cuSparse library. Oct 4, 2015 · There are published examples of Fortran usage for both cublas and cusparse, but I’m not aware of any (yet) for cusolver. When I tried large matrices, such as: (60000, 40000)x (40000, 10000 Sep 9, 2025 · The newest version of the documentation for cusparseXcsrsort and cusparseXcscsort still provides some example code using deprecated functionality, cusparseCreateIdentityPermutation, and removed functionality, cusparseDgthr. x_gpu = cp. When using hipSPARSE on a nvidia machine, it will call the cuSPARSE backend. I then tried writing the most basic CUSPARSE I think of (called test_CUSPARSE_context. CuPy speeds up some operations more than 100X. The cuSPARSE library allows developers to access the computational resources of the NVIDIA graphics processing unit (GPU), although it does not auto-parallelize across multiple GPUs. Here is a program I wrote with reference to forum users’ code, The output of the program is not the solution of the matrix, but the value originally assigned to the B vector. The problem is: I compare the solution from cuSpase with the solution calculated on CPU (Host), but the solution differs from the host solution (calculated with The cuSPARSE APIs provides GPU-accelerated basic linear algebra subroutines for sparse matrix computations for unstructured sparsity. What is this function used for? There is few references on Google. ii) The rocSPARSE repo After detecting that the example code is using the CSR format, S p EQ generates a run-time check (shown in Figure 1d) to guard the running example code and guarantee its preconditions are met. For more information on the available libraries and their uses, visit GPU Accelerated Libraries. Thanks. However I think a csrmv example should be pretty close to bsrmv, such as this one. In this example, S p EQ translates the example code into a series of NVIDIA cuSPARSE library calls that perform SpMV on the GPU [12], shown in Figure 1f. array([1, 2, 3]) x_gpu in the above example is an instance of cupy. For documentation and examples, see the hipSPARSE documentation. Apr 30, 2025 · CUDA Toolkit Documentation 13. The code is setup to perform a non-transpose SpMM operation with the dense matrix either in col- or row-major format and with ALG1 (suggested with col-major) or ALG2 Challenges and Future Directions cuSPARSE is a sparse linear algebra library. Sep 12, 2023 · Please add an example for csrsort when the function (e. Note For portability, ROCm provides the hipSPARSE library. CUDA Library Samples contains examples demonstrating the use of features in the math and image processing libraries, cuBLAS, cuTENSOR, cuSPARSE, cuSOLVER, cuFFT, cuRAND, NPP, nvJPEG About The CUDA Library Samples are released by NVIDIA Corporation as Open Source software under the 3-clause "New" BSD license. The standard approach is to combine the ELL kernel with a COO kernel, which is, for example, the hybrid realization in NVIDIA's cuSPARSE library [NVIDIA Corporation 2018]. This version supports CUDA Toolkit 13. The CUSPARSE API assumes that the input and output data reside in GPU (device) memory, not in CPU (host) memory, unless CPU memory is specifically indicated by the string HostPtr being part of the parameter name of a function (for example, *resultHostPtr in cusparse{S,D,C,Z}doti on page 26). cu file) thank you in advance Jun 11, 2021 · I used the following code to multiply two sparse matrices A and B using SpGEMM, following the sample code. The cuSPARSE APIs provides GPU-accelerated basic linear algebra subroutines for sparse matrix computations for unstructured sparsity. The goal is to optimize the overall performance by using kernels that are runtime-optimal for the respective contributions. The CUSPARSE API assumes that the input and output data reside in GPU (device) memory, DevHostPtr unless specifically indicated otherwise by the string being part of the *resultDevHostPtr cusparse<t>doti parameter name of a function (for example, in ). h> #include “cusparse. gpu cublas nvidia nvml cudnn auto-generate cufft cuda-driver cusolver code-generate curand cusparse nvrtc cublaslt nvtx nvjpeg cuda-hook cuda-hijack cudart nvblas Updated on Dec 11, 2023 C CUSPARSE. I'm trying to do large sparse matrix multiplication. Motivation: we are solving the Poisson equation -divgrad x = b on a rectangular grid. cuSPARSELt Workflow Installation and May 26, 2015 · We are experiencing problems while using cuSOLVER 's cusolverSpScsrlsvchol function, probably due to misunderstanding of the cuSOLVER library. But when I intend to use cusparse and run the official example, which could be found here ( [url]cuSPARSE :: CUDA Toolkit Documentation) … Oct 23, 2024 · Hi, cuSparse csr/bsr solver can do just triangular solve, so it indeed ignores lower or upper part depending on matrix descriptor. NVIDIA In other words, if a program uses cuSPARSE, it should continue to compile and work correctly with newer versions of cuSPARSE without source code changes. Nov 16, 2019 · Figure 2: Example of Compressed Sparse Row (CSR) matrix format Let’s assume for simplicity that there are four threads in each CUDA thread block. The cuSPARSE API assumes that input and output data reside in GPU (device) memory, unless it is explicitly indicated otherwise by the string DevHostPtr in a function parameter's name. After reading the code, I did not find the handling of sparse matrix dense multiplication. cuSPARSE Generic APIs - cusparseDenseToSparse CSR Description This sample demonstrates the usage of cusparseDenseToSparse for performing dense matrix to sparse matrix conversion, where the sparse matrix is represented in CSR (Compressed Sparse Row) storage format. Moreover, the charge distribution on the grid gives a Nov 28, 2019 · The cuSPARSE library allows developers to access the computational resources of the NVIDIA graphics processing unit (GPU), although it does not auto-parallelize across multiple GPUs. But cusparseXcsrilu02_zeroPivot returns cusparse_status_internal_error everytime when I try to start program. 1. The cuSPARSE API assumes that input and output data reside in GPU (device) memory, unless it is explicitly indicated otherwise by the string DevHostPtr in a function parameter's name (for example, the parameter Oct 4, 2024 · Can anyone point me to an example using the sparse double cholesky solver on gpu using C++ and CUDA. Jun 28, 2023 · I adapted a cuSPARSE example (shown below) to benchmark cusparseSpMM. Cheers Terry Nov 3, 2023 · Hello， I am a cusparse beginner and want to call the functions in the cusparse library to solve the tridiagonal matrix problem. 0 and removed in CUDA 12 so no longer available. For ROCm code examples, see ROCm/rocm-examples. One difference is that CUSP is an open-source project hosted at Google Code Archive - Long-term storage for Google Code Project Hosting. According to information from our library team CUSPARSE provides COO/CSR conversion routines, would that be sufficient for your work? CUDA Library Samples. Oct 18, 2013 · I just wanted to know if there are any examples provided by Nvidia or any other trusted source that uses the csrmm function from the cusparse library, to multiply a sparse matrix with a dense matri Jul 22, 2014 · I have already installed CUDA6. Nov 13, 2025 · By integrating cuSPARSE with PyTorch, developers can leverage the high-performance capabilities of GPUs to accelerate sparse matrix computations. Samples for CUDA Developers which demonstrates features in CUDA Toolkit. 0 correctly and could run some other cuda samples. Using the flag “-gpu=cuda11. Provides a collection of basic linear algebra subroutines used for sparse matrices. cuSPARSELt Workflow Installation and Compilation Prerequisites Code Example cuSPARSELt Data Types Opaque Data Structures Enumerators cuSPARSELt Functions Library Management Functions Matrix Descriptor Functions Matmul Descriptor Functions Matmul Algorithm Functions Matmul Functions Helper Functions cuSPARSELt Logging Features Software License A sample code for sparse cholesky solver with cuSPARSE and cuSOLVER library It solves sparse linear system with positive definite matrix using cholesky decomposition Contribute to tpn/cuda-samples development by creating an account on GitHub. cusparseDgthr) is undefined in CUDA 12. For batched computation please visit cusparseSpMM CSR Batched and cusparseSpMM COO Batched. cu): #include <stdio. The Blocked-Ellpack storage format is used to store nonzero values in consecutive blocks and column indices of corresponding nonzero blocks Jan 14, 2019 · Hey, I try to solve a linear equation system coming from FEM algorithm with cuSparse. These solvers were written for a legacy Fortran 77 code with the added Getting Started # In this section, we show how to implement a sparse matrix-matrix multiplication using cuSPARSELt. Nov 28, 2011 · Please note I am not personally familiar with either library. Sep 22, 2023 · I checked the cusparse source code and found that “cusparse_SPGEMM_estimeteMemory” and “cusparse_SPGEMM_getnumproducts” used in SPGEMM_ALG3 are in cusparse. Build status: Code coverage: Julia bindings for the NVIDIA CUSPARSE library. h” int main() { // Initializing the cusparse library cusparseHandle_t Aug 28, 2023 · We read every piece of feedback, and take your input very seriously Please visit cuSPARSE Library Samples - cusparseSpGEMM for a code example for CUSPARSE_SPGEMM_DEFAULT and CUSPARSE_SPGEMM_ALG1, and cuSPARSE Library Samples - memory-optimzed cusparseSpGEMM for a code example for CUSPARSE_SPGEMM_ALG2 and CUSPARSE_SPGEMM_ALG3. Apr 18, 2023 · See cusparseStatus_t for the description of the return status. Static Library Support Starting with CUDA 6. In general, two approaches I can think of: Write the functionality in a C/C++ module, calling Dec 7, 2023 · In looking through the cuSPARSE documentation, I see that this routine was deprecated in CUDA 11. Calling make should be sufficient to build the example program. * This is an example demonstrating usage of the cuSPARSE library to perform a May 20, 2023 · convert your BSR matrix to one of the supported types for this op use cusparse<t>bsrmv() The CUDA library sample codes are here but I don’t know that any pertain to BSR usage. The fortran code for cublas and cusparse can be found in the cuda install directory on your machine (just search for cusparse_fortran. May 20, 2014 · Hi, I am the new guy to use cuSparse Library to compute the sparse matrix computations. Sep 29, 2010 · Dear all, I’m trying to compile the CUSPARSE example in the NVIDIA CUSPARSE library documentation and am running into a problem: none of the cusparse calls work. Jul 21, 2014 · I have already installed CUDA6. CUSPARSE is a high-performance sparse matrix linear algebra library. Mar 19, 2021 · The cuSPARSE library now includes a high-performance block sparse matrix multiplication routine that can exploit NVIDIA GPU dense Tensor Cores for nonzero sub-matrices, significantly outperforming dense computations on Volta and newer architecture GPUs. Jun 2, 2017 · The cuSPARSE API assumes that input and output data reside in GPU (device) memory, unless it is explicitly indicated otherwise by the string DevHostPtr in a function parameter's name (for example, the parameter *resultDevHostPtr in the function cusparse<t>doti ()). I use the example from the cuSparse documentation with LU decomposition (my matrix is non-symmetric) and solve the system with cusparseDcsrsm2_solve. ndarray which is compatible GPU alternative of numpy. NPP – Performance Primitives library. 1 displays achieved SpMV and SpMM performance in GFLOPs by Nvidia's cuSPARSE library on a CUDA Library Samples. jl Build status: Code coverage: Julia bindings for the NVIDIA CUSPARSE library. Lastly, we present a step by step code example with additional comments. Now I met problems to compute the multiplication of two large sparse matrices. The figure shows CuPy speedup over NumPy. Can anyone give a specific example?. The location of each code is as follows in my environment. Architecture specific options There are currently 3 sets of nodes that incorporate GPUs and are available to the SCF users. jl using the CUSPARSE module, which provides GPU-accelerated sparse linear algebra operations. Can someone show me an example or send me a link which has an example code? I tried to find a good example but I couldn't. 8 -cudalib=cusparse” you can revert to using the older CUDA version, but you should investigate finding an alternative method as well. How do I solve this problem? Thank you very much! PROGRAM TDMA use iso_C_binding use Apr 10, 2022 · Hi all, I want to use cuSparse in my CUDA Fortran code. For example, to compile a small application using cuSPARSE against the dynamic library, the following command can be used: A collection of sample implementations for Sparse Matrix-Vector Multiplication (SpMV) using the Compressed Sparse Row (CSR) sparse matrix format on GPU. Then, we describe how to install the library and how to compile it. f90. hipSPARSE is designed to be API compatible with cuSPARSE so it may be easier to port an already existing cuSPARSE project with hipSPARSE. These examples showcase how to leverage GPU-accelerated libraries for efficient computation across various fields. There are several cusparse examples in the CUDA Samples pack, such as the conjugate gradient example, which will show you how to link to cusparse and provide a sample project with MS VS project files. h> #include <cuda_runtime. GPU Accelerated Libraries The cuSPARSE library allows developers to access the computational resources of the NVIDIA graphics processing unit (GPU), although it does not auto-parallelize across multiple GPUs. cuSPARSE is widely used by engineers and scientists working on applications in machine learning, AI, computational fluid dynamics, seismic exploration, and computational sciences. Oct 4, 2021 · i) rocSPARSE should be used where possible as some routines can give better performance with rocSPARSE. Oct 13, 2014 · I tryed to repeat example from Cusparse Libarary Manual (p. In 2 dimensions with a 5 -stencil (1, 1, -4, 1, 1), the Laplacian on the grid provides a (quite sparse) matrix A. I need to transpose a sparse matrix, so I intend to use the function cusparseCsr2cscEx2 () following the document. 1. Oct 28, 2024 · In my current code I am using cusparseSpMM from cuSparse to multiply a float sparse matrix in CSR format and a float dense matrix. Dec 8, 2020 · Structured sparse matrix-matrix multiplication code example Now that you’ve seen the available performance, here’s an example of performing a matrix multiplication with structured sparsity in the cuSPARSELt library using Sparse Tensor Cores in the NVIDIA A100 or GA100 GPU. In this blog post, we will explore the fundamental concepts of cuSPARSE in PyTorch, its usage methods, common practices, and best practices. This portion of the documentation may also be of interest. The CUDA Library Samples are provided by NVIDIA Corporation as Open Source software, released under the Apache 2. Current Supported SpMV Implementations: cuSparse SpMV CUSP CSR-Vector SpMV (supporting warp reduce) LightSpMV Merge-based SpMV in CUB (including a generalized SpMV implementation based on this method) Mar 3, 2017 · Hello, Is there any sample code implementation of the convolution layer using cuSPARSE ? (. cuSparse – Sparse Matrix library. For information about dense linear algebra op Jun 20, 2024 · Please visit cuSPARSE Library Samples - cusparseSpGEMM for a code example for CUSPARSE_SPGEMM_DEFAULT and CUSPARSE_SPGEMM_ALG1, and cuSPARSE Library Samples - memory-optimzed cusparseSpGEMM for a code example for CUSPARSE_SPGEMM_ALG2 and CUSPARSE_SPGEMM_ALG3. cusparseDenseToSparse Documentation B (dense) -> A (csr) Apr 11, 2024 · Please visit cuSPARSE Library Samples - cusparseSpMM CSR and cusparseSpMM COO for a code example. 0 Update 2 Develop, Optimize and Deploy GPU-Accelerated Apps The NVIDIA® CUDA® Toolkit provides a development environment for creating high performance GPU-accelerated applications. A collection of image and signal processing primitives. The cuSolver library is a high-level package based on the cuBLAS and cuSPARSE libraries. Oct 26, 2017 · This document describes the PGI Fortran interfaces to cuBLAS, cuFFT, cuRAND, and cuSPARSE, which are CUDA Libraries used in scientific and engineering applications built upon the CUDA computing architecture. hipSPARSE includes a comprehensive, portable interface that supports multiple backends (including rocSPARSE and cuSPARSE). In both cases, the interfaces to the library can be exposed by adding the line This page explains how to work with sparse matrices in CUDA. The API reference guide for cuSPARSE, the CUDA sparse matrix library. I have used the sample code (by using level 3 routines) as provided at: cuSPARSE :: CUDA Toolkit Documentation The code works fine with (5, 5)x(5, 5) matrices. cuSPARSE is not guaranteed to be backward compatible at the binary level. But when I intend to use cusparse and run the official example, which could be found here ([url]cuSPARSE :: CUDA Toolkit Documentation) Build successed!!! When I run this example, “CUSPARSE Library initialization failed” was occured. g. The code benchmarks the dense matrix memory bandwidth (I have my reasons for that) and I would like to get as close to the full bandwidth as possible. a on Linux. General CSR SpMV implementation works at the The cuSPARSE library allows developers to access the computational resources of the NVIDIA graphics processing unit (GPU), although it does not auto-parallelize across multiple GPUs. Speedup of cuSPARSE Block-SpMM over Dense GEMM in cuBLAS on NVIDIA A100, fp16 in/out, fp32 compute, NN layout, CUDA Toolkit 11. It consists of two modules corresponding to two sets of API: This document describes the NVIDIA Fortran interfaces to cuBLAS, cuFFT, cuRAND, cuSPARSE, and other CUDA Libraries used in scientific and engineering applications built upon the CUDA computing architecture. ndarray. Anyone know how to deal with this kind of problems? Apr 17, 2015 · To avoid any ambiguity on sparse matrix format, the code starts from dense matrices and uses cusparse<t>dense2csr to convert the matrix format from dense to csr. Jan 9, 2019 · How do I use gtsv2 functions of the cusparse library in CUDA Fortran? Asked 6 years, 10 months ago Modified 6 years, 10 months ago Viewed 416 times May 22, 2025 · The sample demonstrates Sparse Matrix - Dense Matrix multiplication = Dense Matrix with Custom Operators, where the sparse matrix is represented in CSR (Compressed Sparse Row) storage format This repository contains an implementation of a parallel algorithm for Sparse-Matrix-Vector-Multiplication for CUDA enabled GPUs. h, while they are not in cusparse. So, which file should I look into to find out the details of handling sparse matrix dense matrix multiplication. For the CSR (compressed-sparse-row) formulation, you could also use the CUSPARSE function for this. 5, the cuSPARSE library is also delivered in a static form as libcusparse_static. Contribute to NVIDIA/CUDALibrarySamples development by creating an account on GitHub. , while CUSPARSE is a closed-source library. Function naming convention Follows the general rule cusparse<Type>[<sparse data format>]<operation>[<sparse data format>] For example, single precision, sparse matrix (in csr storage) x dense vector => cusparseScsrmv double precision, sparse matrix (in csr storage) x dense tall-matrix => cusparseDcsrmm (set of vectors) Chapter 10 contains examples of accessing the cuSPARSE library routines from OpenACC and CUDA Fortran. With the CUDA Toolkit, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based Mar 6, 2024 · Please visit cuSPARSE Library Samples - cusparseSpGEMM for a code example for CUSPARSE_SPGEMM_DEFAULT and CUSPARSE_SPGEMM_ALG1, and cuSPARSE Library Samples - memory-optimzed cusparseSpGEMM for a code example for CUSPARSE_SPGEMM_ALG2 and CUSPARSE_SPGEMM_ALG3. For example, I see the calling to cuSparse library using Nvidia profiling tool. Aug 4, 2020 · The API reference guide for cuSPARSE, the CUDA sparse matrix library. May 20, 2021 · The cuSPARSE library allows developers to access the computational resources of the NVIDIA graphics processing unit (GPU), although it does not auto-parallelize across multiple GPUs. ekad wjsnkf rvnepk ydi eir dquaaa gnjk ubfffi nqe oijp aklqm gth oexjdk hwdm kjdkeji