NVIDIA cuBLAS 库详细介绍 NVIDIA cuBLAS(CUDA Basic Linear Algebra Subprograms library)是 NVIDIA 提供的一套用于 GPU 上的高性能基本线性代数运算的库。它实现了 BLAS 标准中的大部分函数,包括向量和矩阵的操作,如矩阵乘法、求逆、求解线性方程组等。 cuBLAS 的主要特点包括: 高性能:利用 GPU 的并行计算能力,加...
1.cuBLAS简介:CUDA基本线性代数子程序库(CUDA Basic Linear Algebra Subroutine library) cuBLAS库用于进行矩阵运算,它包含两套API,一个是常用到的cuBLAS API,需要用户自己分配GPU内存空间,按照规定格式填入数据,;还有一套CUBLASXT API,可以分配数据在CPU端,然后调用函数,它会自动管理内存、执行计算。既然都用cuda了,其...
4. CUDA Sparse Linear Algebra Library(cuSPARSE):cuSPARSE是CUDA的稀疏线性代数库,提供了各种稀疏矩阵运算函数,如稀疏矩阵乘法、稀疏矩阵转置等。它能够高效地处理大规模稀疏矩阵,节省内存和计算资源。 5. CUDA Performance Primitives(NPP):NPP是CUDA的性能优化库,提供了各种图像和信号处理函数,如图像滤波、图像变换、...
View Code 4. 另外,还有一些额外的库比如NVIDIA cuFFT,NVIDIA cuBLAS (6x to 17x faster performance than the latest MKL BLAS.),EM Photonics CULA Tools(linear algebra library), NVIDIA cuSPARSE,NVIDIA CUDA Math Library https://developer.nvidia.com/gpu-accelerated-libraries...
cuBLAS (CUDA Basic Linear Algebra Subprograms) 基于 CUDA,用于加速通用线性代数运算,并不局限于深度学习。 cuTLASS 主要提供高效的矩阵乘法(GEMM)实现。它把 cuDNN、 cuBLAS 中的矩阵乘法优化抽象为 C++ 模板类,用户可以像“搭积木”一样定制自己的高效矩阵乘法,开发出性能和 cuDNN、 cuBLAS 相当的线性代数算子 ...
GPU-accelerated tensor linear algebra library. Learn More cuDSS GPU-accelerated direct sparse solver library. Learn More CUDA Math API GPU-accelerated standard mathematical function APIs. Learn More AmgX GPU-accelerated linear solvers for simulations and implicit unstructured methods. Learn More NVID...
The cuBLAS library is an implementation of BLAS (Basic Linear Algebra Subprograms) on top of the NVIDIA CUDA runtime. It allows the user to access the computational resources of NVIDIA Graphical Processing Unit (GPU), but does not auto-parallelize across multiple GPUs. ...
options.dense_linear_algebra_library_type = ceres::CUDA; To call cuda, only the simple code above is needed to implement the three methods, respectively the DENSE_QR, DENSE_NORMAL_CHOLESKY and DENSE_SCHUR. It is worth noting that without...
linear algebra library EIGEN Trust region strategy LEVENBERG_MARQUARDT Given Used Linear solver DENSE_QR DENSE_QR Threads 1 1 Linear solver threads 1 1 Cost: Initial 1.075000e+02 Final 1.791438e-14 Change 1.075000e+02 Minimizer iterations 14 Successful steps 14 Unsuccessful steps 0 Time (in ...
minval, matmul, reshape, spread, and transpose on device and managed arrays by mapping Fortran statements to the functions available in the NVIDIA cuTENSOR library, a first-of-its-kind, GPU-accelerated, tensor linear algebra library providing tensor contraction, reduction, and element-wise operations...