Business was brisk in the exhibition hall Dr Keren Bergman delivers her keynote

commented: ‘Summit’s AI-optimised hardware also gives researchers an incredible platform for analysing massive datasets and creating intelligent software to accelerate the pace of discovery.’

Competition in AI drives computing performance Nvidia has been at the forefront of AI development for a number of years and this trend shows no sign of abating. The company continued to showcase both hardware and software development that is driving the potential for AI and also real- world scientific applications. At ISC Nvidia showcased its AI solutions

and services, including the DGX-2 and the Nvidia GPU cloud (NGC), alongside talks based on the future of GPU technology in HPC and AI, NVSwitch and the new Oak Ridge supercomputer Titan. Nvidia users working with the Nvidia GPU cloud can now use 35 deep learning, high-performance computing, and visualisation containers from NGC. Containers allow scientists and researchers to deploy applications on the cloud easily and reliably. Over the past three years, containers have become a crucial tool in deploying applications on a shared cluster and speeding the work, especially for researchers and data scientists running AI workloads. Nvidia was demonstrating some of | @scwmagazine

these containers as there have been several new applications released on the NGC since SC17 in November last year. These new HPC and visualisation containers include CHROMA, CANDLE, PGI and VMD, which have been added to the NGC. This is in addition to eight containers, including NAMD, GROMACS and ParaView, launched at the previous year’s conference. The aim for this is similar to other

areas of software tool and ecosystem development for Nvidia. By providing these containers they are giving some level of assurance that an application will work and deliver a certain performance based on Nvidia hardware. This helps scientists and researchers get set up using AI applications but it also helps to generate experience in these areas, as users develop a familiarity and experience working with Nvidia hardware. Intel is also making inroads into the AI

market with several announcements at ISC regarding the company’s plans for future development in both AI and its roadmap for HPC. Intel was showing applications running on its Xeon Scalable processors for use in AI workloads. These chips are designed specifically for AI/ML and will allow much faster speeds for inferencing and training neural networks. Intel hosted several talks and demos at its booth, including a brain tumour screening simulation that is trained with high-resolution images using AI running on Intel Xeon Scalable processors. Intel has also begun developing a

software stack for artificial intelligence, which aims to develop optimised libraries for various popular AI frameworks for many different AI workloads, such as speech and image recognition, language translation and object detection.

“Artificial intelligence holds great promise for medical progress including genomics”

Intel also plans to use its FPGA

technology for HPC/AI workloads, particularly in compression, image/object recognition and genome sequencing. Intel’s efforts to develop an ecosystem

around AI have already begun to impact scientific research. Intel and the Institut Curie, a French research centre, announced a partnership in May. That aims to use AI in the implementation of bioinformatics tools, pipelines and techniques to improve the use of molecular profiling across both research and clinical oncology research. The research centre will work with Intel

to define high-performance computing and artificial intelligence infrastructure. ‘Artificial intelligence holds great promise for medical progress, including genomics,’ said Brian Krzanich, former Intel CEO. ‘The Intel-Institut Curie collaboration is one more example of Intel’s commitment to the development of bold artificial intelligence research for the good of humanity.’ ‘Collaborating with Intel, Institut Curie

will develop, use and implement innovative bioinformatics technologies to improve time to diagnosis, diagnostic accuracy, targeted treatment recommendations, and provide a better understanding of application needs to develop features that are needed for the healthcare sector,’ said Emmanuel Barillot, head of the Institut Curie Bioinformatics platform and director of the Bioinformatics, Biostatistics, Epidemiology and Computational Systems Research Unit.

August/September 2018 Scientific Computing World 11

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