machine_learning   11929

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[1706.03292] Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters
Deep learning models can take weeks to train on a single GPU-equipped machine, necessitating scaling out DL training to a GPU-cluster. However, current distributed DL implementations can scale poorly due to substantial parameter synchronization over the network, because the high throughput of GPUs allows more data batches to be processed per unit time than CPUs, leading to more frequent network synchronization. We present Poseidon, an efficient communication architecture for distributed DL on GPUs. Poseidon exploits the layered model structures in DL programs to overlap communication and computation, reducing bursty network communication. Moreover, Poseidon uses a hybrid communication scheme that optimizes the number of bytes required to synchronize each layer, according to layer properties and the number of machines. We show that Poseidon is applicable to different DL frameworks by plugging Poseidon into Caffe and TensorFlow. We show that Poseidon enables Caffe and TensorFlow to achieve 15.5x speed-up on 16 single-GPU machines, even with limited bandwidth (10GbE) and the challenging VGG19-22K network for image classification. Moreover, Poseidon-enabled TensorFlow achieves 31.5x speed-up with 32 single-GPU machines on Inception-V3, a 50% improvement over the open-source TensorFlow (20x speed-up).
machine_learning  TensorFlow 
yesterday by amy
UC Irvine Machine Learning Repository
UC Irvine Machine Learning Repository!

We currently maintain 394 data sets as a service to the machine learning community. You may view all data sets through our searchable interface.
machine_learning  dataset 
yesterday by slavko
AWS public datasets
AWS hosts a variety of public datasets that anyone can access for free.
Previously, large datasets such as satellite imagery or genomic data have required hours or days to locate, download, customize, and analyze. When data is made publicly available on AWS, anyone can analyze any volume of data without needing to download or store it themselves. These datasets can be analyzed using AWS compute and data analytics products, including Amazon EC2, Amazon Athena, AWS Lambda and Amazon EMR.
machine_learning  dataset 
yesterday by slavko
Datasets « Deep Learning
These datasets can be used for benchmarking deep learning algorithms
database  data  ai  datasets  machine_learning 
2 days ago by rrraul

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