Seven Things You Might Not Know about Numba

Features, Analytics, Big Data, CUDA, Numba, Python

Nadeem Mohammad, posted Oct 02 2017

One of my favorite things is getting to talk to people about GPU computing and Python. The productivity and interactivity of Python combined with the high performance of GPUs is a killer combination for many problems in science and engineering.

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Gradient Boosting, Decision Trees and XGBoost with CUDA

Features, CUDA, Gradient Boosting, Machine Learning, XGBoost

Nadeem Mohammad, posted Sep 11 2017

Gradient boosting is a powerful machine learning algorithm used to achieve state-of-the-art accuracy on a variety of tasks such as regression, classification and ranking.

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Pro Tip: Linking OpenGL for Server-Side Rendering

Pro Tip, In-situ, OpenGL, Server-side, Visualization

Nadeem Mohammad, posted Aug 16 2017

Visualization is a great tool for understanding large amounts of data, but transferring the data from an HPC system or from the cloud to a local workstation for analysis can be a painful experience.

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Scaling Keras Model Training to Multiple GPUs

Features, Deep Learning, Keras, MxNet

Nadeem Mohammad, posted Aug 16 2017

Keras is a powerful deep learning meta-framework which sits on top of existing frameworks such as TensorFlow and Theano. Keras is highly productive for developers; it often requires 50% less code to define a model than native APIs of deep learning

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Deep Learning Hyperparameter Optimization with Competing Objectives

Features, Deep Learning

Nadeem Mohammad, posted Aug 03 2017

In this post we’ll show how to use SigOpt’s Bayesian optimization platform to jointly optimize competing objectives in deep learning pipelines on NVIDIA GPUs more than ten times faster than traditional approaches like random search.

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