cuBLAS Insights

What is cuBLAS?

cuBLAS is an implementation of BLAS (Basic Linear Algebra Subprograms) on top of the NVIDIA CUDA runtime. It allows for significant acceleration of linear algebra operations, such as matrix multiplication, matrix inversion, and solving linear systems, by utilizing the parallel processing capabilities of NVIDIA GPUs. It's commonly used in scientific computing, deep learning, and other areas that require high-performance linear algebra.

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What other technologies are related to cuBLAS?

cuBLAS Competitor Technologies

ROCm

ROCm is AMD's GPU computing platform, and includes libraries that compete with CUDA and cuBLAS, such as rocBLAS.

mentioned alongside cuBLAS in 9% (97) of relevant job posts

HIP

HIP is a C++ dialect that allows developers to write code that can run on both NVIDIA and AMD GPUs. It competes with CUDA and cuBLAS by providing an alternative platform.

mentioned alongside cuBLAS in 4% (67) of relevant job posts

OpenCL

OpenCL is a parallel programming framework that can be used to perform similar operations as cuBLAS on different hardware. It is a competitor to CUDA and cuBLAS.

mentioned alongside cuBLAS in 1% (108) of relevant job posts

cuBLAS Complementary Technologies

cuDNN

cuDNN is a library for deep neural networks, which utilizes cuBLAS for its BLAS operations. Thus, it complements cuBLAS.

mentioned alongside cuBLAS in 23% (231) of relevant job posts

CUTLASS

CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance GEMM. It complements cuBLAS by providing low-level building blocks.

mentioned alongside cuBLAS in 34% (106) of relevant job posts

TensorRT

TensorRT is an SDK for high-performance deep learning inference. It optimizes deep learning models and utilizes cuBLAS for its BLAS operations, thus complementing cuBLAS.

mentioned alongside cuBLAS in 3% (113) of relevant job posts