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Case Study: Supercomputing Natural Gas Turbine Generators for Huge Boosts in Efficiency

Hyperion Research has published a new case study on how General Electric engineers were able to nearly double the efficiency of gas turbines with the help of supercomputing simulation. “With these advanced modeling and simulation capabilities, GE was able to replicate previously observed combustion instabilities. Following that validation, GE Power engineers then used the tools to design improvements in the latest generation of heavy-duty gas turbine generators to be delivered to utilities in 2017. These turbine generators, when combined with a steam cycle, provided the ability to convert an amazing 64% of the energy value of the fuel into electricity, far superior to the traditional 33% to 44%.”

Opportunities Abound: HPC and Machine Learning for Energy Exploration

The is the first entry in a five-part insideHPC series that takes an in-depth look at how machine learning, deep learning and AI are being used in the energy industry. Read on to find out how machine learning is driving energy exploration. “Any tool that reduces the time needed to understand where the deposits are located can save a company millions of dollars.”

Squeezing Light could be key to Quantum Computing

“Scientists at Hokkaido University and Kyoto University have developed a theoretical approach to quantum computing that is 10 billion times more tolerant to errors than current theoretical models. Their method brings us closer to developing quantum computers that use the diverse properties of subatomic particles to transmit, process and store extremely large amounts of complex information.”

How Deep Learning Tech Can Contribute to Success

Frameworks, applications, libraries and toolkits—journeying through the world of deep learning can be daunting. If you’re trying to decide whether or not to begin a machine or deep learning project, there are several points that should first be considered. This is the fourth article in a five-part series that covers the steps to take before launching a machine learning startup. This post covers how deep learning is contributing to success across a variety of industries.

DDN and Parabricks Accelerate Genome Analysis

Today DDN announced a Parabricks technology solution that provides massive acceleration for analysis of human genomes. The breakthrough platform combines GPU supercomputing performance with DDN’s Parallel Flash Data Platforms for fastest time to results, and enables unprecedented capabilities for high-throughput genomics analysis pipelines. The joint solution also ensures full saturation of GPUs for maximum efficiency and provides analysis capabilities that previously required thousands of CPUs to engage.

What Next? Entering the World of Machine Learning

Frameworks, applications, libraries and toolkits—journeying through the world of deep learning can be daunting. If you’re trying to decide whether or not to begin a machine or deep learning project, there are several points that should first be considered. This is the final article in a five-part series that covers the steps to take before launching a machine learning startup. This article provides a variety of resources to employ when first exploring machine learning. 

How Exascale will Move Earthquake Simulation Forward

In this video from the HPC User Forum in Tucson, David McCallen from LBNL describes how exascale computing capabilities will enhance earthquake simulation for improved structural safety. “With the major advances occurring in high performance computing, the ability to accurately simulate the complex processes associated with major earthquakes is becoming a reality. High performance simulations offer a transformational approach to earthquake hazard and risk assessments that can dramatically increase our understanding of earthquake processes and provide improved estimates of the ground motions that can be expected in future earthquakes.”

Industry Insights: Download the Results of our AI & HPC Perceptions Survey

The results from our HPC & AI peception survey are here. “90 percent of all respondents felt that their business will ultimately be impacted by AI. Although almost all respondents see AI as playing a role in the future of the business, the survey also revealed the top three industries that will see the most impact. Healthcare came in first, followed by life sciences, and finance/transportation tied in third place. The possibilities of AI are seemingly endless. And the shift has already begun.”

NREL Report Evaluates LiquidCool Solutions for the Datacenter

NREL researchers are testing immersive liquid cooling technologies that could potentially bring huge energy savings to HPC datacenters. With worldwide datacenters consuming an estimated 70 billion kWh per year, a disruptive energy-saving solution is needed, and a liquid-submerged server (LSS) technology from LiquidCool Solutions might be the answer. “The testing confirmed that the LSS technology could not only maintain target temperatures under heavy computational load, but that the hot liquid could be used to heat buildings more efficiently than NREL’s current solution.”

Resource Management Across the Private/Public Cloud Divide

This is the final entry in a insideHPC series of features that explores new resource management solutions for workload convergence, such as Bright Cluster Manager by Bright Computing. This article highlights how resource management systems that can manage clusters on-premises or in the cloud greatly simplify cluster management. That way, different tools do not have to be learned for managing a cluster based on whether it is located in the company data center or in the cloud.