Category Archives: Test Drive

What Can You Do with a $15k NVIDIA Data Science Workstation? – Change Healthcare Data Science

NVIDIA’s Data Science Workstation Platform is designed to bring the power of accelerated computing to a broad set of data science workflows. Recently, we found out what happens when you lend a talented data scientist (with a serious appetite for … Continue reading

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

GPU-accelerated HPC Containers with Singularity

Fighting with application installations is frustrating and time consuming. It’s not what domain experts should be spending their time on. And yet, every time users move their project to a new system, they have to begin again with a re-assembly … 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

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

Common PCI-Express Myths for GPU Computing Users

At Microway we design a lot of GPU computing systems. One of the strengths of GPU-compute is the flexibility PCI-Express bus. Assuming the server has appropriate power and thermals, it enables us to attach GPUs with no special interface modifications. We can … Continue reading

Introducing the NVIDIA Tesla K80 GPU Accelerator (Kepler GK210)

NVIDIA has once again raised the bar on GPU computing with the release of the new Tesla K80 GPU accelerator.  With up to 8.74 TFLOPS of single-precision performance with GPU Boost, the Tesla K80 has massive capability and leading density. … Continue reading

How to Benchmark GROMACS GPU Acceleration on HPC Clusters

We know that many of our readers are interested in seeing how molecular dynamics applications perform with GPUs, so we are continuing to highlight various packages. This time we will be looking at GROMACS, a well-established and free-to-use (under GNU GPL) … Continue reading

Benchmark MATLAB GPU Acceleration on NVIDIA Tesla K40 GPUs

MATLAB is a well-known and widely-used application – and for good reason. It functions as a powerful, yet easy-to-use, platform for technical computing. With support for a variety of parallel execution methods, MATLAB also performs well. Support for running MATLAB … Continue reading