cuBLAS
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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.
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.
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.
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.
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cuBLAS Complementary Technologies
cuDNN
cuDNN is a library for deep neural networks, which utilizes cuBLAS for its BLAS operations. Thus, it complements cuBLAS.
CUTLASS
No summary available
CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance GEMM. It complements cuBLAS by providing low-level building blocks.
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.
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Which job functions commonly mention cuBLAS?
Machine Learning
0.1% of all Machine Learning jobs mention cuBLAS
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jobs on Sumble
AI Engineer
26 AI Engineer jobs mention cuBLAS
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jobs on Sumble
Software Architect
18 Software Architect jobs mention cuBLAS
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jobs on Sumble
Software Engineer
90 Software Engineer jobs mention cuBLAS
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jobs on Sumble
Engineer
124 Engineer jobs mention cuBLAS
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jobs on Sumble
Which organizations are mentioning cuBLAS?
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