Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Woodpecker-DL: Accelerating Deep Neural Networks via Hardware-Aware
  Multifaceted Optimizations   Accelerating deep model training and inference is crucial in practice.
Existing deep learning frameworks usually concentrate on optimizing training
speed and pay fewer attentions to inference-specific optimizations. Actually,
model inference differs from training in terms of computation, e.g. parameters
are refreshed each gradient update step during training, but kept invariant
during inference. These special characteristics of model inference open new
opportunities for its optimization. In this paper, we propose a hardware-aware
optimization framework, namely Woodpecker-DL (WPK), to accelerate inference by
taking advantage of multiple joint optimizations from the perspectives of graph
optimization, automated searches, domain-specific language (DSL) compiler
techniques and system-level exploration. In WPK, we investigated two new
automated search approaches based on genetic algorithm and reinforcement
learning, respectively, to hunt the best operator code configurations targeting
specific hardware. A customized DSL compiler is further attached to these
search algorithms to generate efficient codes. To create an optimized inference
plan, WPK systematically explores high-speed operator implementations from
third-party libraries besides our automatically generated codes and singles out
the best implementation per operator for use. Extensive experiments
demonstrated that on a Tesla P100 GPU, we can achieve the maximum speedup of
5.40 over cuDNN and 1.63 over TVM on individual convolution operators, and run
up to 1.18 times faster than TensorRT for end-to-end model inference.

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The categories of this paper are: chem-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: q-bio
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The categories of this paper are: quant-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: patt-sol
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The categories of this paper are: supr-con
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The categories of this paper are: nucl-th
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The categories of this paper are: gr-qc
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The categories of this paper are: ao-sci
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The categories of this paper are: math-ph
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The categories of this paper are: adap-org
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The categories of this paper are: atom-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: comp-gas
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The categories of this paper are: econ