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Cloud Adoption for HPC: Trends and Opportunities

This whitepaper is an insideHPC Special Research Report sponsored by Univa. “Today many organizations solve their most difficult computational challenges by creating their own on-premises, compute-intensive, high performance data center. The latest hardware and software innovations have removed barriers that prevented many organizations from embracing HPC solutions. With more enterprises extending their own on-premises clusters into the cloud with hybrid configurations, finding the right tools for managing and scheduling workflows and automatically controlling cost remains a critical challenge.”

Data Center Transformation: Why a Workload-Driven and Scalable Architecture Matters

The QCT Platform on Demand (QCT POD) combines advanced technology with a unique user experience to help enterprises reach better performance and gain more insights. “With flexibility and scalability, QCT POD enables enterprises to address a broader range of HPC, Deep Learning, and Data Analytic demands that fulfill various applications.”

Deep Learning for Natural Language Processing – Choosing the Right GPU for the Job

In this new whitepaper from our friends over at Exxact Corporation we take a look at the important topic of deep learning for Natural Language Processing (NLP) and choosing the right GPU for the job. Focus is given to the latest developments in neural networks and deep learning systems, in particular a neural network architecture called transformers. Researchers have shown that transformer networks are particularly well suited for parallelization on GPU-based systems.

Leadership Performance with 2nd-Generation Intel Xeon Scalable Processors

According to Intel, its new 2nd generation Intel Xeon Scalable Processor family includes Intel Deep Learning Boost for AI deep learning inference acceleration, fresh features and support for Intel Octane DC (data center) persistent memory, and more. Learn more about the offerings in a new issue of Parallel Universe Magazine.

Parallelism in Python: Directing Vectorization with NumExpr

According to a new edition of Parallel Universe Magazine, from Intel, Python has several pathways to vectorization. These range from just-intime (JIT) compilation with Numba 1 to C-like code with Cython. A chapter from a recent edition of Parallel Universe Magazine, explores parallelism in Python.

Exploring Bright Cluster Manager on NVIDIA DGX Systems

Artificial Intelligence (AI) is rapidly becoming an essential business and research tool, providing valuable new insights into corporate data and delivering those insights with high velocity and accuracy. While these AI capabilities add significant value to our lives, they are the most demanding workloads in modern computing history. Download the new report from Bright Computing to explore how NVIDIA DGX and Bright Cluster Manager are designed to deliver more of what AI infrastructure users need. 

GPUs for Oil and Gas Firms: Deriving Insights from Petabytes of Data

Adoption of GPU-accelerated computing can offer oil and gas firms significant ROI today and pave the way to gain additional advantage from future technical developments. To stay competitive, these companies need to be able to derive insights from petabytes of sensor, geolocation, weather, drilling, and seismic data in milliseconds. A new white paper from Penguin Computing explores how GPUs are spurring innovation and changing how hydrocarbon businesses address data processing needs.

Best Practices for Building, Deploying & Managing HPC Clusters

In today’s markets, a successful HPC cluster can be a formidable competitive advantage. And many are turning to these tools to stay competitive in the HPC market. That said, these systems are inherently very complex, and have to be built, deployed and managed properly to realize their full potential. A new report from Bright Computing explore best practices for HPC clusters. 

GPUs Address Growing Data Needs for Finance & Insurance Sectors

A new whitepaper from Penguin Computing contends “a new era of supercomputing” has arrived — driven primarily by the emergence of graphics processing units or GPUs. The tools once specific to gaming are now being used by investment and financial services to gain greater insights and generate actionable data. Learn how GPUs are spurring innovation and changing how today’s finance companies address their data processing needs. 

Exploring the ROI Potential of GPU Supercomputing

The growing prevalence of artificial intelligence and machine learning is putting heightened focus on the quantities of data that organizations have recently accumulated — as well as the value potential in this data. Companies looking to gain a competitive edge in their market are turning to tools like graphic processing units – or GPUs – to ramp up computing power. That’s according to a new white paper from Penguin Computing.