Will this be the year of artificial intelligence, when the technology comes into its own for mainstream business? There are big pushes for AI in manufacturing, agriculture, healthcare and many other industry sectors. But why now? Please share your insights in our Reader Survey.
Robotics and Deep Learning applications were front and center at GTC Japan this week, where 2600 attendees lined up to hear the latest on GPU technologies. The age of AI is here,” said Jen-Hsun Huang, founder and CEO of NVIDIA. “GPU deep learning ignited this new wave of computing where software learns and machines reason. […]
Today NVIDIA announced APAC’s first deployment of NVIDIA DGX-1 deep learning supercomputers CSIRO in Australia. “There is a growing interest from research groups to adopt machine learning techniques to support their projects,” said Angus Macoustra, executive manager for Scientific Computing at CSIRO. “CSIRO research projects are already using the DGX-1 systems, and in time, it is expected that machine learning will have applicability across all our areas of research and be used by hundreds of researchers.”
This may indeed be the year of artificial intelligence, when the technology came into its own for mainstream businesses. “But will other companies understand if AI has value for them? Perhaps a better question is “Why now?” This question centers on both the opportunity and why many companies are scared about missing out.”
Two University of Wyoming graduate students earned a trip to the SC16 conference in November by virtue of winning the poster contest at the recent Rocky Mountain Advanced Computing Consortium (RMACC) High Performance Computing Symposium. “I hope to receive good exposure to the most recent advancements in the field of high-performance computing,” Kommera says.
“Our high-performance computing solutions enable deep learning, engineering, and scientific fields to scale out their compute clusters to accelerate their most demanding workloads and achieve fastest time-to-results with maximum performance per watt, per square foot, and per dollar,” said Charles Liang, President and CEO of Supermicro. “With our latest innovations incorporating the new NVIDIA P100 processors in a performance and density optimized 1U and 4U architectures with NVLink, our customers can accelerate their applications and innovations to address the most complex real world problems.”
Today Amazon Web Services announced the availability of P2 instances, a new GPU instance type for Amazon Elastic Compute Cloud designed for compute-intensive applications that require massive parallel floating point performance, including artificial intelligence, computational fluid dynamics, computational finance, seismic analysis, molecular modeling, genomics, and rendering. With up to 16 NVIDIA Tesla K80 GPUs, P2 instances are the most powerful GPU instances available in the cloud.
Today Nvidia announced the general availability of CUDA 8 toolkit for GPU developers. “A crucial goal for CUDA 8 is to provide support for the powerful new Pascal architecture, the first incarnation of which was launched at GTC 2016: Tesla P100,” said Nvidia’s Mark Harris in a blog post. “One of NVIDIA’s goals is to support CUDA across the entire NVIDIA platform, so CUDA 8 supports all new Pascal GPUs, including Tesla P100, P40, and P4, as well as NVIDIA Titan X, and Pascal-based GeForce, Quadro, and DrivePX GPUs.”