HPC Top 5 StoriesWeekly Insights into the World of High Performance Computing

The combination of HPC and AI has paved the way for groundbreaking

discoveries in science, medicine, etc.

Here are the “Top Five” storieshighlighting what’s hot in HPC and AI.

1HPC TOP 5

AI Computing Boom Drives Growth for NVIDIAArtificial intelligence is one of the hottest technology trends for 2017. And perhaps no company in the AI sector is hotter than NVIDIA, which has pushed from the desktop into the data center, evolving into a major player in high performance computing.NVIDIA’s graphics processing (GPU) technology has been one of the biggest beneficiaries of the rise of specialized computing, gaining traction with workloads in supercomputing, artificial intelligence (AI) and connected cars. This trend is expected to accelerate in 2017, with more custom chips being introduced to target these workloads.

LEARN MORE Visit the NVIDIA Tesla Where to Buy Server Page.

2HPC TOP 5

Kinetica Aims to Broaden Appeal of GPU ComputingKinetica today unveiled a new iteration of its in-memory, GPU-accelerated database that it says will help to democratize data science and traditional business intelligence by simultaneously running SQL-based queries and machine learning/deep learning workloads on the same data.The San Francisco company says it accomplished the feat by delivering new user defined functions (UDFs). The UDFs have direct access to the CUDA APIs that the Kinetica database uses, and can receive data, do arbitrary functions, and save output to a global table in a distributed manner, the company says. This will allow SQL-loving data analysts to access the processing power of Kinetica clusters through simple API calls that wrapper the SQL queries, it says.

LEARN MORETo learn more about the most advanced data center ever built, read about the NVIDIA Tesla P100.

3HPC TOP 5

Expanding Choices for PowerAI Developers with TensorFlowThe latest version of PowerAI including TensorFlow has been optimized and validated on GPU-accelerated Linux on Power platforms running Ubuntu 16.04 and the NVIDIA CUDA 8 software platform — and our optimizations take particular advantage of NVIDIA Tesla P100 GPUs connected to POWER8 with the NVIDIA NVLink interconnect on the IBM Power Systems S822LC for HPC.

This updated release also incorporates Google’s Bazel build tool, which is used in the development of many advanced TensorFlow models.

LEARN MORE Learn how TensorFlow on GPUs will fulfill all your deep learning needs. Get started today.

4HPC TOP 5

Artificial Intelligence MarketInitially, AI was considered as topic for academicians, though in recent years with development of various technologies, AI has turned into reality and is influencing many lives and businesses. Additionally, evolution of various other supplementary technologies such as cloud computing, machine learning and cognitive computing are collectively paving the growth of the market for AI.

Many IT giants and start-ups are investing heavily in development of AI software solutions and hardware products.

LEARN MORELearn more about the DGX-1, the world’s first AI supercomputer in a box.

5HPC TOP 5

People to Watch 2017: Ian BuckIan Buck is NVIDIA’s General Manager for GPU Computing Software, responsible for all engineering, 3rd party enablement, and developer marketing activities for GPU Computing at NVIDIA. Ian joined NVIDIA in 2004 and created CUDA, which remains the established leading platform for accelerated based parallel computing. Before joining NVIDIA, Ian was the development lead on Brook which was the forerunner to generalized computing on GPUs. He holds a Ph.D. in Computer Science from Stanford University and B.S.E from Princeton University.

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