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Adrian Cockcroft Presents: Shrinking Microservices to Functions

In this fascinating talk, Cockcroft describes how hardware networking has reshaped how services like Machine Learning are being developed rapidly in the cloud with AWS Lamda. “We’ve seen the same service oriented architecture principles track advancements in technology from the coarse grain services of SOA a decade ago, through microservices that are usually scoped to a more fine grain single area of responsibility, and now functions as a service, serverless architectures where each function is a separately deployed and invoked unit.”

Addison Snell Presents: HPC Computing Trends

Addison Snell presented this deck at the Stanford HPC Conference. “Intersect360 Research returns with an annual deep dive into the trends, technologies and usage models that will be propelling the HPC community through 2017 and beyond. Emerging areas of focus and opportunities to expand will be explored along with insightful observations needed to support measurably positive decision making within your operations.”

Deep Learning & HPC: New Challenges for Large Scale Computing

“In recent years, major breakthroughs were achieved in different fields using deep learning. From image segmentation, speech recognition or self-driving cars, deep learning is everywhere. Performance of image classification, segmentation, localization have reached levels not seen before thanks to GPUs and large scale GPU-based deployments, leading deep learning to be a first class HPC workload.”

IBM Machine Learning Platform Comes to the Private Cloud

“Machine Learning and deep learning represent new frontiers in analytics. These technologies will be foundational to automating insight at the scale of the world’s critical systems and cloud services,” said Rob Thomas, General Manager, IBM Analytics. “IBM Machine Learning was designed leveraging our core Watson technologies to accelerate the adoption of machine learning where the majority of corporate data resides. As clients see business returns on private cloud, they will expand for hybrid and public cloud implementations.”

Defining AI, Machine Learning, and Deep Learning

“In this guide, we take a high-level view of AI and deep learning in terms of how it’s being used and what technological advances have made it possible. We also explain the difference between AI, machine learning and deep learning, and examine the intersection of AI and HPC. We also present the results of a recent insideBIGDATA survey to see how well these new technologies are being received. Finally, we take a look at a number of high-profile use case examples showing the effective use of AI in a variety of problem domains.”

Video: Computing of the Future

Jeffrey Welser from IBM Research Almaden presented this talk at the Stanford HPC Conference. “Whether exploring new technical capabilities, collaborating on ethical practices or applying Watson technology to cancer research, financial decision-making, oil exploration or educational toys, IBM Research is shaping the future of AI.”

Startup Video: Architecting Flash for Scale and Performance in HPC

“High Performance Computing (HPC) is considered the unlimited class of computing where performance is all that matters. Increasingly, business enterprises are looking to apply the technology and techniques from HPC to help them solve their complex business challenges. Weka.IO’s CTO, Liran Zvibel, will discuss how affordable HPC class storage performance and scale can be achieved using Flash technology and a hardware independent software architecture.”

DDN Drives Discoveries at Van Andel Research Institute

“Deploying DDN’s end-to-end storage solution has allowed us to elevate the standard of protection, increase compliance and push the boundaries of science on a single, highly scalable storage platform,” said Ramjan. “We’ve also saved hundreds of thousands of dollars by centralizing the storage of our data-intensive research and a dozen data-hungry scientific instruments on DDN. With all these advantages it is easy to see why DDN is core to our operation and a major asset to our scientists.”

Supermicro Deploys 30,000+ MicroBlade Servers for 1.06 PUE Datacenter

A technology-leading Fortune 100 company has deployed over 30,000 Supermicro MicroBlade servers, at its Silicon Valley data center facility with a Power Use Effectiveness (PUE) of 1.06, to support the company’s growing compute needs. Compared to a traditional data center running at 1.49 PUE, or more, the new datacenter achieves an 88percent improvement in overall energy efficiency. When the build out is complete at a 35 megawatt IT load power, the company is targeting $13.18M in savings per year in total energy costs across the entire datacenter.

NVIDIA Rolls Out New Quadro Pascal GPUs

“Professional workflows are now infused with artificial intelligence, virtual reality and photorealism, creating new challenges for our most demanding users,” said Bob Pette, vice president of Professional Visualization at NVIDIA. “Our new Quadro lineup provides the graphics and compute performance required to address these challenges. And, by unifying compute and design, the Quadro GP100 transforms the average desktop workstation with the power of a supercomputer.”