| Architecture | NVIDIA GPU | Instance type | Instance name | Number of GPUs | GPU Memory (per GPU) | GPU Interconnect (NVLink / PCIe) | Thermal Design Power (TDP) from nvidia-smi |
Tensor Cores (mixed-precision) | Precision Support | CPU Type | Nitro based |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Ampere | A100 | P4 | p4d.24xlarge | 8 | 40 GB | NVLink gen 3 (600 GB/s) | 400W | Tensor Cores (Gen 3) | FP64, FP32, FP16, INT8, BF16, TF32 | Intel Xeon Scalable (Cascade Lake) | Yes |
| Ampere | A10G | G5 | g5.xlarge | 1 | 24 GB | NA ( |
Hemanth Kumar M Hemanthkumar2112
shashankprasanna
/ aws_gpu_list.md
Last active
May 7, 2024 04:42
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| import tensorflow as tf | |
| # create and train a keras neural network | |
| classifier = tf.keras.models.Sequential([ | |
| tf.keras.layers.Dense(units=1, input_shape=[1]), | |
| tf.keras.layers.Dense(units=28, activation='relu'), | |
| tf.keras.layers.Dense(units=1) | |
| ]) | |
| classifier.compile(optimizer='sgd', loss='mean_squared_error') | |
| classifier.fit(x=[-1, 0, 1], y=[-3, -1, 1], epochs=5) |