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Intel's Deep Learning Boost (DL Boost) is a marketing name for instruction set architecture features on the x86-64 designed to improve performance on deep learning tasks such as training and inference. DL Boost consists of two sets of features: * AVX-512 VNNI, 4VNNIW, or AVX-VNNI: fast multiply-accumulation mainly for convolutional neural networks. * AVX-512 BF16: lower-precision bfloat16 floating-point numbers for generally faster computation. Operations provided include conversion to/from float32 and dot product. DL Boost features were introduced in the Cascade Lake architecture.

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  • DL Boost (en)
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  • Intel's Deep Learning Boost (DL Boost) is a marketing name for instruction set architecture features on the x86-64 designed to improve performance on deep learning tasks such as training and inference. DL Boost consists of two sets of features: * AVX-512 VNNI, 4VNNIW, or AVX-VNNI: fast multiply-accumulation mainly for convolutional neural networks. * AVX-512 BF16: lower-precision bfloat16 floating-point numbers for generally faster computation. Operations provided include conversion to/from float32 and dot product. DL Boost features were introduced in the Cascade Lake architecture. (en)
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  • Intel's Deep Learning Boost (DL Boost) is a marketing name for instruction set architecture features on the x86-64 designed to improve performance on deep learning tasks such as training and inference. DL Boost consists of two sets of features: * AVX-512 VNNI, 4VNNIW, or AVX-VNNI: fast multiply-accumulation mainly for convolutional neural networks. * AVX-512 BF16: lower-precision bfloat16 floating-point numbers for generally faster computation. Operations provided include conversion to/from float32 and dot product. DL Boost features were introduced in the Cascade Lake architecture. A TensorFlow-based benchmark run on the Google Cloud Platform Compute Engine shows improved performance and reduced cost compared to previous CPUs and to GPUs, especially for small batch sizes. (en)
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