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Xeon cpu e5 2640 v4

Manufactured by NVIDIA
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The Xeon CPU E5-2640 v4 is a high-performance server processor developed by Intel. It features 10 cores, 20 threads, and a clock speed of up to 2.4 GHz. The processor is designed for use in demanding workloads such as virtualization, data analysis, and high-performance computing.

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Lab products found in correlation

Gk210gl, by NVIDIA (1 mentions) Titan xp, by NVIDIA (1 mentions)

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Xeon E5 CPU (2 citations)

2 protocols using xeon cpu e5 2640 v4

1

Custom-mode PC-based Deep Learning

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For all calculations, a custom-mode PC with a CPU (Core i7-8700 Intel Xeon CPU E5-2640 v4 @ 2.40 GHz) and 4 GPU (Tesla K80, NVIDIA GK210GL) are used. The installed OS is Ubuntu 16.04 LTS. We use TensorFlow- version 1.12.0 (https://github.com/tensorflow/tensorflow/releases/tag/v1.12.0) and Keras version 2.2.5 (https://github.com/keras-team/keras/releases/tag/2.2.5) to build the models.
Ye T., Li S, & Zhang Y. (2021). Genomic pan-cancer classification using image-based deep learning. Computational and Structural Biotechnology Journal, 19, 835-846.
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2

Geant4-based Simulations with PyTorch

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All simulations were implemented in Gate version 8.0 [16] , using Geant4 version 10.3 [17] . Neural network operations (training, samples generation) were implemented in Python with the PyTorch framework [18] using CUDA GPU acceleration. Once the network is trained, it can be read and used within Gate/Geant4 thanks to a newly developed Gate module exploiting the PyTorch C++ API [19] . Source code is open-source and will be available in the next Gate release. Computations were performed on an Intel Xeon CPU E5-2640 v4 @ 2.40GHz and an NVIDIA Titan Xp (GP102-450-A1) with 12 GB memory.
Sarrut D., Krah N, & Létang J.M. (2019). Generative adversarial networks (GAN) for compact beam source modelling in Monte Carlo simulations. Physics in medicine and biology, 64(21).
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