Building a Computing Architecture for Drug Discovery

We recently had the pleasure of helping Jason Roszik and his colleagues at the University of Texas MD Anderson Cancer Center in developing a high-throughput architecture supporting their work in identifying combination therapies for cancer. This work sits at the interface of some major technology, processing and clinical trends, and it was quite an eye-opener — as well as a motivation — for us on how to use Cray-developed systems and processing technologies to build a useful and productive high-throughput IT architecture. The first trend, of course, is next-generation sequencing (NGS). Costs are going down and sequencing throughput is going up dramatically, to where today’s NGS companies state they can process tens of human genomes a ... [ Read More ]

Scalable Deep Learning with BigDL on the Urika-XC Software Suite

Deep-learning-based AI approaches have resulted in remarkable advancements in diverse fields such as computer vision, speech recognition, natural language processing and bioinformatics. As part of our continuing efforts to offer customers a single system that can host both simulations and advanced data analytics, we recently launched the Cray® Urika®-XC analytics software suite, bringing graph analytics, deep learning and robust big data analytics tools to the company’s flagship line of Cray® XC™ supercomputers. An important piece of the Urika-XC suite is the BigDL deep learning framework. BigDL is a distributed deep learning library for Apache Spark™ developed inside Intel and contributed back to the open source community. ... [ Read More ]

Artificial Intelligence: Five Trends for 2018

As we start 2018 here at Cray, we believe artificial intelligence and, more specifically, deep learning will continue to dominate the emerging technology landscape conversation (and I know that some might argue block chain technologies have already surpassed AI, but that’s another conversation). Since we have several subject matter experts at Cray, I thought it might be a good idea to reach out to the Cray AI team and ask them, “What is a trend for AI or deep learning you expect in 2018?” Rangan Sukumar, analytic architect in our CTO office: • Mathematical/algorithmic innovations will dictate hardware/system requirements: Algorithmic cleverness, mathematical approximations and sub-precision tweaks have enabled a 7-10x speed-up, mostly ... [ Read More ]

Why Artificial Intelligence Needs HPC

As we work with our customers on their artificial intelligence (AI) journeys, we are finding that a range of approaches are being taken by distinct organizations to implement AI. We recently had an opportunity to speak with Brian Dolan, chief scientist and co-founder of an AI startup — Deep 6 AI — to understand their interest in the Chapel parallel programming language, as well as why they view AI as a high-performance computing (HPC) problem. First a bit of background on Deep 6 AI and Chapel. Deep 6 AI is an artificial intelligence company whose primary mission is to find more patients faster for clinical trials — an important part of drug development and drug discovery. In 2016, Deep 6 AI was chosen by the ... [ Read More ]

AI: Science Fact vs. Science Fiction (Part 3: Predictive Policing)

It started with robots. In the first part of this 3-article series about artificial intelligence in science fiction vs. real-life AI, we talked about robots — both real and as depicted in sci-fi starting in the early 20th century. Then we visited advanced AI like the mutinous shipboard computer HAL 9000. But that’s just fiction, right? When does it start getting real? We’ll conclude with a brief look at today’s robot police and computer-assisted crime prediction. It turns out RoboCop is real ... sort of. Leave it to Dubai to deploy the world’s first robot police officer. This life-sized robotic patrolman, put into service earlier this year, can collect evidence and identify wanted criminals as it patrols the busiest parts of ... [ Read More ]