This post discusses the Total Cost of Ownership (TCO) for a variety of Lambda A100 servers and clusters. We calculate the TCO for individual Hyperplane-A100 servers, compare the cost with renting a AWS p4d.24xlarge instance, and walk through the cost of building and operating A100 clusters.
Introducing the Lambda Echelon, a GPU cluster designed for AI. It comes with the compute, storage, network, power, and support you need to tackle large scale deep learning tasks. Echelon offers a turn-key solution to faster training, faster hyperparameter search, and faster inference.
This post uses our Total Cost of Ownership (TCO) calculator to examine the cost of a variety of Lambda Hyperplane-16 clusters. We have the option to include 100 Gb/s EDR InfiniBand networking, storage servers, and complete rack-stack-label-cable service.
Resource utilization tracking can help machine learning engineers improve their software pipeline and model performance. This blog discusses how to use Weights & Biases to inspect the efficiency of TensorFlow training jobs.
This presentation is a high-level overview of the different types of training regimes you'll encounter as you move from single GPU to multi GPU to multi node distributed training. It describes where the computation happens, how the gradients are communicated, and how the models are updated and communicated.
Titan V vs. RTX 2080 Ti vs. RTX 2080 vs. Titan RTX vs. Tesla V100 vs. GTX 1080 Ti vs. Titan Xp - TensorFlow benchmarks for neural net training.
RTX 2080 Ti vs. RTX 2080 vs. Titan RTX vs. Tesla V100 vs. Titan V vs. GTX 1080 Ti vs. Titan Xp benchmarks neural net training.
How to stress test a system for simultaneous GPU and CPU loads using two stress tools, stress and gpu_burn, and three monitoring tools, htop, iotop and nvidia-smi.
Titan RTX vs. 2080 Ti vs. 1080 Ti vs. Titan Xp vs. Titan V vs. Tesla V100. For this post, Lambda engineers benchmarked the Titan RTX's deep learning performance vs. other common GPUs. We measured the Titan RTX's single-GPU training performance on ResNet50, ResNet152, Inception3, Inception4, VGG16, AlexNet, and SSD.
We open sourced the benchmarking code we use at Lambda so that anybody can reproduce the benchmarks that we publish or run their own.
What's the best GPU for Deep Learning? The 2080 Ti. We benchmark the 2080 Ti vs the Titan V, V100, and 1080 Ti.
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