{"id":17289686,"url":"https://github.com/olk/mnist-performance","last_synced_at":"2026-05-08T13:44:05.958Z","repository":{"id":150515146,"uuid":"230991998","full_name":"olk/mnist-performance","owner":"olk","description":"performance test of MNIST hand writings usign MXNet + 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MNIST performance tests\n\nThe projects tests the performance of MXNet and Tensorflow using MNIST data.\n\n\n## project structure\n\n    ├── LICENSE\n    ├── README.md                  \u003c- Top-level README for developers using this project\n    ├── mnist_mx_gluon.py          \u003c- MXNet + Gluon\n    ├── mnist_mx_gluon_mgpu.py     \u003c- MXNet + Gluon + multi-gpu\n    ├── mnist_mx_gluon_hvd.py      \u003c- MXNet + Gluon + Horovod\n    ├── mnist_mx_keras.py          \u003c- MXNet + Keras\n    ├── mnist_mx_keras_mgpu.py     \u003c- MXNet + Keras + multi-gpu (multi_gpu_model())\n    ├── mnist_mx_sym.py            \u003c- MXNet + symbol/module API\n    ├── mnist_mx_sym_mgpu.py       \u003c- MXNet + symbol/module API + multi-gpu\n    ├── mnist_tf_keras.py          \u003c- Tensorflow + Keras\n    └── mnist_tf_keras_mirrored.py \u003c- Tensorflow + Keras + multi-gpu (MirroredStrategy())\n\n\n### MXNet Info\n    Version      : 1.5.1\n    Directory    : /home/graemer/Projekte/MXNet/apache-mxnet-src-1.5.1-incubating/python/mxnet\n    Num GPUs     : 2\n\n### System Info\n    system       : Linux\n    node         : e5lx\n    release      : 5.4.3-arch1-1\n    version      : #1 SMP PREEMPT Fri, 13 Dec 2019 09:39:02 +0000\n\n### Hardware Info\n    Architektur:                     x86_64\n    CPU Operationsmodus:             32-bit, 64-bit\n    Byte-Reihenfolge:                Little Endian\n    Adressgrößen:                    46 bits physical, 48 bits virtual\n    CPU(s):                          32\n    Liste der Online-CPU(s):         0-31\n    Thread(s) pro Kern:              2\n    Kern(e) pro Socket:              8\n    Sockel:                          2\n    NUMA-Knoten:                     2\n    Anbieterkennung:                 GenuineIntel\n    Prozessorfamilie:                6\n    Modell:                          79\n    Modellname:                      Intel(R) Xeon(R) CPU E5-2620 v4 @ 2.10GHz\n    Stepping:                        1\n    CPU MHz:                         1197.887\n    Maximale Taktfrequenz der CPU:   3000,0000\n    Minimale Taktfrequenz der CPU:   1200,0000\n    BogoMIPS:                        4192.42\n    Virtualisierung:                 VT-x\n    L1d Cache:                       512 KiB\n    L1i Cache:                       512 KiB\n    L2 Cache:                        4 MiB\n    L3 Cache:                        40 MiB\n    NUMA-Knoten0 CPU(s):             0-7,16-23\n    NUMA-Knoten1 CPU(s):             8-15,24-31\n\n\n## test results\n\nmultigpu [[Horovod]] (2 GPUs): `horovodrun -np 2 -H localhost:2 python mnist_mx_gluon_hvd.py`\n\n | framework                 | duration | accuracy |\n |---------------------------|----------|----------|\n | mnist_mx_gluon.py         | 14.2s    | 0.9926   |\n | mnist_mx_keras.py         | 16.4s    | 0.9931   |\n | mnist_mx_sym.py           | 16.8s    | 0.9924   |\n | mnist_tf_keras.py         | 17.6s    | 0.9932   |\n | mnist_mx_gluon_ds.py      | 17.6s    | 0.9902   |\n |                           |          |          |\n | mnist_mx_gluon_mgpu.py    | 7.2s     | 0.9926   |\n | mnist_mx_gluon_hvd.py     | 9.0s     | 0.9963   |\n | mnist_mx_sym_mgpu.py      | 10.9s    | 0.9923   |\n | mnist_mx_keras_mgpu.py    | 11.4s    | 0.9927   |\n | mnist_tf_keras_mgpu.py    | 12.7s    | 0.9921   |\n | mnist_mx_gluon_ds_mgpu.py | 15.2s    | 0.9906   |\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Folk%2Fmnist-performance","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Folk%2Fmnist-performance","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Folk%2Fmnist-performance/lists"}