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The true cost of AI innovation

“As the world’s attention has shifted to climate change, the field of AI is beginning to take note of its carbon cost. Research done at the Allen Institute for AI by Roy Schwartz et al. raises the question of whether efficiency, alongside accuracy, should become an important factor in AI research, and suggests that AI scientists ought to deliberate if the massive computational power needed for expensive processing of models, colossal amounts of training data, or huge numbers of experiments is justified by the degree of improvement in accuracy.”

NVIDIA Adds GPU and AI Expertise to COVID-19 HPC Consortium

A task force of NVIDIA computer scientists has joined the COVID-19 High Performance Computing Consortium, which brings together leaders from the U.S. government, industry and academia to accelerate research using the world’s most powerful HPC resources. “The consortium’s objective is to accelerate development of effective methods to detect, contain and treat the coronavirus. It will support researchers by providing access to 30 supercomputers with over 400 petaflops of compute performance.”

Video: High-Performance Memory For AI And HPC

In this video, Frank Ferro from Rambus examines the current performance bottlenecks in HPC, drilling down into power and performance for different memory options. “HBM2E offers the capability to achieve tremendous memory bandwidth. Four HBM2E stacks connected to a processor will deliver over 1.6 TB/s of bandwidth. And with 3D stacking of memory, high bandwidth and high capacity can be achieved in an exceptionally small footprint. Further, by keeping data rates relatively low, and the memory close to the processor, overall system power is kept low.”

HPC at Scale Enabled by DDN A3i and NVIDIA SuperPOD

William Beaudin from DDN gave this talk at GTC Digital. “Enabling high performance computing through the use of GPUs requires an incredible amount of IO to sustain application performance. We’ll cover architectures that enable extremely scalable applications through the use of NVIDIA’s SuperPOD and DDN’s A3I systems. The groundbreaking performance delivered by the DGX SuperPOD enables the rapid training of deep learning models at great scale.”

Scientists Look to Exascale and Deep Learning for Developing Sustainable Fusion Energy

Scientists from Princeton Plasma Physics Laboratory are leading an Aurora ESP project that will leverage AI, deep learning, and exascale computing power to advance fusion energy research. “With a suite of the world’s most powerful path-to-exascale supercomputing resources at their disposal, William Tang and colleagues are developing models of disruption mitigation systems (DMS) to increase warning times and work toward eliminating major interruption of fusion reactions in the production of sustainable clean energy.”

Interview: Under Secretary Paul Dabbar on the COVID-19 HPC Consortium

The DOE laboratory complex has many core capabilities that can be applied to addressing the threats posed by COVID-19. “This public-private partnership includes the biggest players in advanced computing from government, industry, and academia. At launch, the consortium includes five DOE laboratories, industry leaders like IBM, Microsoft, Google, and Amazon, and preeminent U.S. universities like MIT, RPI, and UC San Diego. And within a week, we’ve already received more than a dozen requests from other organizations to join the consortium.”

Video: NVIDIA to Accelerate the HPC-AI Convergence

Gunter Roeth from NVIDIA gave this talk at ML4HPC 2020. “The growing adoption of NVIDIA Volta GPU by the Top500 Supercomputers highlights the need of computing acceleration for this HPC & AI convergence. Many projects today demonstrate the benefit of AI for HPC, in terms of accuracy and time to solution, in many domains such as Computational Mechanics, Earth Sciences, Life Sciences, Computational Chemistry, and Computational Physics. NVIDIA today for instance, uses Physics Informed Neural Networks for the heat sink design in our DGX system.”

Registration Opens for Stanford HPC Conference Virtual Event

Registration is now open for the Stanford HPC Conference. The two day ‘condensed’ agenda combines thought leadership and practical insights on HPC, AI, Data Science and much more. The virtual event takes place April 21-22. “The Stanford High Performance Computing Center in collaboration with the HPC-AI Advisory Council invite you to join the annual Stanford Conference as an entirely virtual experience.”

NCSA Joins Nationwide Collaboration to Combat COVID-19

NCSA is joining, Microsoft Corporation, and research institutions across the country as part of the new Digital Transformation Institute ( DTI). This new institute, a multi-disciplinary effort focused on artificial intelligence and advanced computing, will initially accept proposals related to the abatement of COVID-19, and mitigating risks from future pandemics using AI. “This new institute will greatly expand the use of computing and data to improve the world, starting with bringing together a consortium of leading institutions to address the COVID-19 crisis.”

Video: Quantum Computing and Supercomputing, AI, Blockchain

Shahin Khan from gave this talk at the Washington Quantum Computing Meetup. “A whole new approach to computing (as in, not binary any more), quantum computing is as promising as it is unproven. Quantum computing goes beyond Moore’s law since every quantum bit (qubit) doubles the computational power, similar to the famous wheat and chessboard problem. So the payoff is huge, even though it is, for now, expensive, unproven, and difficult to use. But new players will become more visible, early use cases and gaps will become better defined, new use cases will be identified, and a short stack will emerge to ease programming.”