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AI Workflow Scalability through Expansion

In this special guest feature, Tim Miller, Braden Cooper, Product Marketing Manager at One Stop Systems (OSS), suggests that for AI inferencing platforms, the data must be processed in real time to make the split-second decisions that are required to maximize effectiveness.  Without compromising the size of the data set, the best way to scale the model training speed is to add modular data processing nodes.

Choosing the Best Data Flow Design for GPU Accelerated Applications

In this sponsored article from our friends over at Supermicro, we discusses how deciding on the correct type of GPU accelerated computation hardware depends on many factors. One particularly important aspect is the data flow patterns across the PCIe bus and between GPUs and Intel® Xeon® Scalable processors. These factors, along with some application insights are explored below.

Transform Your Business with the Next Generation of Accelerated Computing

In this white paper, you’ll find a compelling discussion regarding how Supermicro servers optimized for NVIDIA A100 GPUs are solving the world’s greatest HPC and AI challenges. As the expansion of HPC and AI poses mounting challenges to IT environments, Supermicro and NVIDIA are equipping organizations for success, with world-class solutions to empower business transformation. The Supermicro team is continually testing and validating advanced hardware featuring optimized software components to support a rising number of use cases.

Transform Your Business with the Next Generation of Accelerated Computing

In this white paper we discuss how Supermicro servers optimized for NVIDIA A100 GPUs are solving the world’s greatest HPC and AI challenges. As the expansion of HPC and AI poses mounting challenges to IT environments, Supermicro and NVIDIA are equipping organizations for success, with world-class solutions to empower business transformation. We are continually testing and validating advanced hardware featuring optimized software components to support a rising number of use cases.

UMass Dartmouth Speeds Research with Hybrid Supercomputer from Microway

UMass Dartmouth’s powerful new cluster from Microway affords the university five times the compute performance its researchers enjoyed previously, with over 85% more total memory and over four times the aggregate memory bandwidth. “The UMass Dartmouth cluster reflects a hybrid design to appeal to a wide array of the campus’ workloads. “Over 50 nodes include Intel Xeon Scalable Processors, DDR4 memory, SSDs and Mellanox ConnectX-5 EDR 100Gb InfiniBand. A subset of systems also feature NVIDIA V100 GPU accelerators. Equally important are a second subset of POWER9 with 2nd Generation NVLink- based- IBM Power Systems AC922 Compute nodes.”

NEC Delivers HPC Cluster to RWTH Aachen University in Germany

Today NEC announced that RWTH Aachen University in Germany has started operations of a new HPC cluster. Called CLAIX-2018 the system augments the university’s existing CLAIX-2016 installation. “RWTH Aachen is one of the most renowned universities in Germany, and this project is a lighthouse project not only for the HPC datacentre, but also for NEC,” said Yuichi Kojima, Vice President HPC EMEA at NEC Deutschland.

Video: IBM Powers Ai at the GPU Technology Conference

In this video from the GPU Technology Conference, Sumit Gupta from IBM describes how IBM is powering production-level Ai and Machine Learning. “IBM PowerAI provides the easiest on-ramp for enterprise deep learning. PowerAI helped users break deep learning training benchmarks AlexNet and VGGNet thanks to the world’s only CPU-to-GPU NVIDIA NVLink interface. See how new feature development and performance optimizations will advance the future of deep learning in the next twelve months, including NVIDIA NVLink 2.0, leaps in distributed training, and tools that make it easier to create the next deep learning breakthrough.”

Video: NVIDIA Showcases Programmable Acceleration of multiple Domains with one Architecture

In this video from GTC 2019 in Silicon Valley, Marc Hamilton from NVIDIA describes how accelerated computing is powering AI, computer graphics, data science, robotics, automotive, and more. “Well, we always make so many great announcements at GTC. But one of the traditions Jensen has now started a few years ago is coming up with a new acronym to really make our messaging for the show very, very simple to remember. So PRADA stands for Programmable Acceleration Multiple Domains One Architecture. And that’s really what the GPU has become.”

Mellanox HDR 200G InfiniBand Speeds Machine Learning with NVIDIA

Today Mellanox announced that its HDR 200G InfiniBand with the “Scalable Hierarchical Aggregation and Reduction Protocol” (SHARP) technology has set new performance records, doubling deep learning operations performance. The combination of Mellanox In-Network Computing SHARP with NVIDIA 100 Tensor Core GPU technology and Collective Communications Library (NCCL) deliver leading efficiency and scalability to deep learning and artificial intelligence applications.

Agenda Posted for ExaComm 2018 Workshop in Frankfurt

The ExaComm 2018 workshop has posted their Speaker Agenda. Held in conjunction with ISC 2018, the Fourth International Workshop on Communication Architectures for HPC, Big Data, Deep Learning and Clouds at Extreme Scale takes place June 28 in Frankfurt. ” The goal of this workshop is to bring together researchers and software/hardware designers from academia, industry and national laboratories who are involved in creating network-based computing solutions for extreme scale architectures. The objectives of this workshop will be to share the experiences of the members of this community and to learn the opportunities and challenges in the design trends for exascale communication architectures.”