We’re excited to announce the latest version of our Bitfusion Ubuntu 14 Chainer AMI is now available in the AWS Marketplace.
Chainer is a Python framework for developing neural networks that can leverage CUDA for GPU computation. It supports a variety of network architectures including feed-forward nets, convnets, recurrent nets and recursive nets, and focuses on an intuitive experience with easy debugging. This latest AMI release includes Chainer 1.21, which includes a variety of new features, bug fixes, and performance enhancements.
Stay tuned for future updates to our Chainer AMI, which will likely next include the new Chainer 2.0 major release -- currently still in alpha. Chainer 2.0 will have CuPy separated out as a separate project and new features such as unified configuration.
For many, Jupyter is the primary interface for performing data work. In the latest AMI, we’ve included an extensive Jupyter notebook tutorial for getting started with Chainer. If this is your first time using Chainer, or you are still experimenting, the guide does a great job walking through how to tap into the core capabilities of the framework.
Regardless of whether you prefer Python 2 or Python 3, we’ve added new and updated tools, libraries, and frameworks to support and handle both.
When working with Chainer, there are many libraries that provide complementary functionality. In order to provide a truly comprehensive data science and deep learning toolset, we’re including them all by default.
AWS recently announced their next generation GPU P2 instances, which provide up to 16 NVIDIA K80 GPUs, 64 vCPUs and 732 GiB of host memory. In our 2016.02 release of the Bitfusion Chainer AMI and more recent, we included updated NVIDIA drivers, the CUDA toolkit, and CUDNN support, allowing you to tap into these new powerful instances.
Try out these new additions and enhancements in the AWS marketplace; all our AMIs come with a 5 day software free trial: Bitfusion Ubuntu 14 Chainer AMI.