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Composable Kernel (CK) library aims to provide a programming model for writing performance critical kernels for machine learning workloads across multiple architectures including GPUs, CPUs, etc, through general purpose kernel languages, like HIP C++. CK utilizes two concepts to achieve performance portability and code maintainability: - A tile-based programming model - Algorithm complexity reduction for complex ML operators, using innovative technique we call "Tensor Coordinate Transformation".
| Package | Summary | Distribution | Download |
| composable_kernel-7.0.1-2.fc44.x86_64.html | Performance Portable Programming Model for Machine Learning Tensor Operators | Fedora Rawhide for x86_64 | composable_kernel-7.0.1-2.fc44.x86_64.rpm |
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