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Author Archives: John Murphy
One-shot Learning Methods Applied to Drug Discovery with DeepChem
Experimental data sets for drug discovery are sometimes limited in size, due to the difficulty of gathering this type of data. Drug discovery data sets are expensive to obtain, and some are the result of clinical trials, which might not … Continue reading
DeepChem – a Deep Learning Framework for Drug Discovery
A powerful new open source deep learning framework for drug discovery is now available for public download on github. This new framework, called DeepChem, is python-based, and offers a feature-rich set of functionality for applying deep learning to problems in … Continue reading
Deep Learning Benchmarks of NVIDIA Tesla P100 PCIe, Tesla K80, and Tesla M40 GPUs
Sources of CPU benchmarks, used for estimating performance on similar workloads, have been available throughout the course of CPU development. For example, the Standard Performance Evaluation Corporation has compiled a large set of applications benchmarks, running on a variety of … Continue reading
More Tips on OpenACC Acceleration
One blog post may not be enough to present all tips for performance acceleration using OpenACC. So here, more tips on OpenACC acceleration are provided, complementing our previous blog post on accelerating code with OpenACC. Further tips discussed here are: … Continue reading
Deep Learning Applications in Science and Engineering
Over the past decade, and particularly over the past several years, Deep learning applications have been developed for a wide range of scientific and engineering problems. For example, deep learning methods have recently increased the level of significance of the … Continue reading
Accelerating Code with OpenACC and the NVIDIA Visual Profiler
Comprised of a set of compiler directives, OpenACC was created to accelerate code using the many streaming multiprocessors (SM) present on a GPU. Similar to how OpenMP is used for accelerating code on multicore CPUs, OpenACC can accelerate code on … Continue reading
Deep Learning Frameworks: A Survey of TensorFlow, Torch, Theano, Caffe, Neon, and the IBM Machine Learning Stack
The art and science of training neural networks from large data sets in order to make predictions or classifications has experienced a major transition over the past several years. Through popular and growing interest from scientists and engineers, this field … Continue reading
Keras and Theano Deep Learning Frameworks
Here we will explore how to use the Theano and Keras Python frameworks for designing neural networks in order to accomplish specific classification tasks. In the process, we will see how Keras offers a great amount of leverage and flexibility … Continue reading
Caffe Deep Learning Tutorial using NVIDIA DIGITS on Tesla K80 & K40 GPUs
In this Caffe deep learning tutorial, we will show how to use DIGITS in order to train a classifier on a small image set. Along the way, we’ll see how to adjust certain run-time parameters, such as the learning rate, … Continue reading