Learning to Optimize Tensor Programsarxiv.org/abs/1805.08166 Abstract 深度学习的迅猛发展,在计算机视觉、自然语言处理等领域取得令人瞩目的突破,为了让工程师和算法科学家快速实现深度学习模型,一系列深度学习框架应运而生,如:TensorFlow、Pytorch、Keras、MxNet等。这些框架都有不小的受众,强大的公司及社区支持。
Learning to optimize tensor programs Halide: A language and compiler for optimizing parallelism, locality, and recomputation in image processing pipelines. Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations Tensor comprehensions: Framework-agnostic high-performance machine lear...
Learning to Optimize The repository archives papers regarding the combination of combinatorial optimization and machine learning and corresponding reading notes. For this intersection of machine learning and combinatorial optimization, we name it Learning to Optimize. Corresponding authos: Mingxuan Yuan, Huili...
a tuner trained to optimize tensor programs for a specific vendor’s CPU in a deep learning workload may not be as effective in generating efficient tensor programs for a CPU from a different vendor. To address this challenge, transfer learning has proven beneficial by assimilating context from ...
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[ ] ; 17 parent_transpose ← GetOutputTranspose(target_model, parent, new_node) ; // Emitted by parent at Line 33 18 if parent_transpose ≠ NULL then 19 1 ← old_in_layout [ ] ; 20 2 ← new_in_layout [ ] ; 21 if IsInverse(parent_transpose, 1, 2) then // Optimize parent_...
The TensorFlow Lite toolset optimizes TensorFlow models to run well on such devices, by letting you choose tradeoffs between model size and accuracy. A smaller model (that is, 12MB versus 25MB, or even 100+MB) is less accurate, but the loss is generally small, and it’s more than ...
See below for a list of the possible input parameters to these programs and what they do. FixedL program input parameters and code features fixedLoptimizes a matrix product state (MPS) with a label index on the central tensor, similar to what is described in the paper arxiv:1605.05775. Th...
Learning to Optimize Tensor Programs, 2018 ProGraML, 2021 Hallide, 2013 search Chameleon, 2020 AdaTune, 2020 DynaTune, 2021 Ansor, 2020 MetaTune, 2021 Spatial Sharing of GPU for Autotuning DNN models, 2020 Black-box auto-tuning COBAYN, 2016 ...
and apply these representations to optimize tensor programs used in deep learning applications. I will then describe the system improvements we made to enable diverse hardware backends. TVM, our end-to-end system, delivers performance across hardware back-ends that are competitive withstate-of-the-...