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Arm Total compute Solutions 2023 brings enhancements across the board

Mobile devices are essential to our daily lives. They allow us to create and consume immersive, AI-powered experiences that are constantly pushing the limits of what is possible. Arm is at the heart of many of all of our mobile computers - smartphones, tablets, handheld consoles, and even many more. ....

Arm Compute Library , Arm Total Compute Solutions , Arm Immortalis G ,

Introducing Arm Total Compute Solutions 2023: Cortex-X4, A720 and A520, Immortalis-G715 GPU

Mobile devices play a crucial role in every aspect of our digital lives. With just a handheld device, we have the power to create and consume immersive experiences that are enhanced by artificial inte. ....

Seogjun Lee , Dan Kochpatcharin , Yujian Shi , Stuart Pann , Mediatek Dimensity , Dave Burke , Congbing Li , Nick Rapp , Ip Henry Duan , Immortalis Gpus , Samul Deng , Xuezhong Zeng , Bryan Chang , Application Processor Ap Development , Wireless Communications Business Unit , Arm Total Compute Solutions , Intel Foundry Services , Research Development Mgmt Dept , Arm Compute Library , Head Of The Design Infrastructure Management Division , Samsung Electronics , Xiaomi Group , Arm Immortalis , Vertex Shading , Genshin Impact , Arm Mali G ,

PyTorch 2.0: Our next generation release that is faster, more Pythonic and Dynamic as ever

An open source machine learning framework that accelerates the path from research prototyping to production deployment. ....

Pytorch Dtensor , Mkldnn One , Pytorch Distributedtensor Dtensor , Single Program Multiple Devices , Arm Compute Library , Team Pytorch , Pytorch Conference , Dynamic Shapes , Accelerated Transformers , Better Transformers , Performance Shaders , Pytorch Transformer , Transformer Decoders , Transformer Encoder , Self Attention , Accelerated Pytorch , Python Frame Evaluation Hooks , Stable Diffusion , With Pytorch , Memory Efficient Attention , Geomean Speedup , Message Passing , Compressed Sparse Row , Automatic Mixed Precision , Torch Distributedtensor , Pytorch Tensor Parallelism ,

PyTorch 1.13 release, including beta versions of functorch and improved support for Apple's new M1 chips.

We are excited to announce the release of PyTorch® 1.13 (release note)! This includes Stable versions of BetterTransformer. We deprecated CUDA 10.2 and 11.3 and completed migration of CUDA 11.6 and 11.7. Beta includes improved support for Apple M1 chips and functorch, a library that offers composable vmap (vectorization) and autodiff transforms, being included in-tree with the PyTorch release. This release is composed of over 3,749 commits and 467 contributors since 1.12.1. We want to sincerely thank our dedicated community for your contributions.

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