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Faster Path to HPC Enabled with Intel Select Solutions for Simulation & Modeling

HPC clusters used for simulation and modeling today in government, academic, and corporate institutions drive scientific discovery and engineering innovation. This sponsored post from Bill Magro, chief technologist for HPC, and HPC solutions lead at Intel Corp., explores how Intel, OEMs, systems integrators, and ISVs partner to reduce deployment barriers through pre-configured and validated HPC systems. 

Achieving Parallelism in Intel Distribution for Python with Numba

The rapid growth in popularity of Python as a programming language for mathematics, science, and engineering applications has been amazing. Not only is it easy to learn, but there is a vast treasure of packaged open source libraries out there targeted at just about every computational domain imaginable. This sponsored post from Intel highlights how today’s enterprises can achieve high levels of parallelism in large scale Python applications using the Intel Distribution for Python with Numba. 

3 Ways to Unlock the Power of HPC and AI

A growing number of commercial businesses are implementing HPC solutions to derive actionable business insights, to run higher performance applications and to gain a competitive advantage. Complexities abound as HPC becomes more pervasive across industries and markets, especially as companies adopt, scale, and optimize both HPC and Artificial Intelligence (AI) workloads. Bill Mannel, VP & GM HPC & AI Solutions Segment at Hewlett Packard Enterprise, walks readers through three strategies to ensure HPC and AI success.

Intel Optimized Libraries Accelerate Deep Learning Applications on Intel Platforms

Whatever the platform, getting the best possible performance out of an application always presents big challenges. This is especially true when developing AI and machine learning applications on CPUs. This sponsored post from Intel explores how to effectively train and execute machine learning and deep learning projects on CPUs.

Using Inference Engines to Power AI Apps Audio, Video and more

With the demand for intelligent solutions like autonomous driving, digital assistants, recommender systems, enterprises of every type are demanding AI powered – applications for surveillance, retail, manufacturing, smart cities and homes, office automation, autonomous driving, and more coming every day. Increasingly, AI applications are powered by smart inference-based inputs. This sponsored post from Intel explores how inference engines can be used to power AI apps, audio, video and highlights the capabilities of Intel’s Distribution of OpenVINO (Open Visual Inference and Neural Network Optimization) toolkit.

Developing Next Generation Autonomous Vehicles using ‘AI on the Fly’

The quest to remove humans from behind the wheel with truly autonomous vehicles will drive billions of dollars in investment by car manufacturers and transportation service providers to develop and acquire the required technology. In this sponsored post from One Stop Systems, Tim Miller, Vice President of Strategic Development, explores how autonomous vehicles will change the transportation landscape, and the role AI has in this shift. 

The Convergence of HPC and AI Workloads Requires Flexibility and Performance

Finding the best solution to meet the requirements for intertwined HPC and AI workloads requires us tolook at the overall platform benefits versus the benefits of individual technologies. With exascale on the horizon, the blending of HPC and AI algorithms, and ever-increasing data sets, having an overall robust platform is more important than ever. Intel makes the case for HPC and AI to share a common platform. 

The Convergence of HPC & AI: Why it’s Great for Supercomputing and the Enterprise

By the end of 2019, worldwide AI spend is expected to reach $35 billion and more than double by 2022, according to IDC. While AI market projections may be speculative, there’s a general consensus the investment will be significant and the impact will be transformative. Lenovo explores innovation at the convergence of HPC and AI, including early detection of prostate cancer, mitigating the impact of deforestation, preventing visual impairment and more. 

Exascale for Everyone

The exascale hype has been gaining a lot of steam in the press lately, and for good reason. Ever since the petascale barrier was broken in 2008, technology users, companies and research institutions have set their ‘sites’ on the holy grail of computing milestones. In this guest article, Matt Ziegler, Director HPC & AI Product Management, HPC Product Marketing at Lenovo, explores the evolution of and potential of exascale computing.

Converging Workflows Pushing Converged Software onto HPC Platforms

Are we witnessing the convergence of HPC, big data analytics, and AI? Once, these were separate domains, each with its own system architecture and software stack, but the data deluge is driving their convergence. Traditional big science HPC is looking more like big data analytics and AI, while analytics and AI are taking on the flavor of HPC.