Enterprise IT vendor IBM today said it is offering NVIDIA Tesla K80 dual-GPU accelerators on bare metal cloud servers.
This new cloud GPU capability is important for startups and research facilities because IBM Cloud provides a supercomputing option that supports discovery and insight for customers in a variety of industries, including genomics, data analysis, machine learning and deep learning.
“Our global network of data centers, connectivity features, bare metal servers, and GPU offerings meet the rigorous requirements of most supercomputing workloads,” said Marc Jones, CTO for SoftLayer, an IBM company. “By introducing the K80 accelerator on IBM Cloud, we’re giving our customers an even more powerful tool to run demanding applications.”
New York University (NYU) recently used NVIDIA Tesla K80 GPU accelerators on IBM Cloud to support a deep-learning course.
Startup MapD uses Tesla K80 accelerators on IBM Cloud for data and analytics – enabling multiple users to query and visualize multibillion row data sets with latencies measured in milliseconds, achieving orders-of-magnitude increases in speed over other solutions.
Artomatix uses Tesla K80 accelerators on IBM Cloud to apply machine-learning and big-data concepts to art creation, enabling computers to manage many tedious and time-consuming aspects of the process and allowing artists to focus on creating more dynamic games and films. The Artomatix platform enables a single artist to do the work of a team, disrupting traditional art and animation workflows in the video game and movie industries.
Tesla K80’s dual-GPU architecture includes a large memory that provides more teraflops of double-precision computing performance and gigabytes of memory in a single server to accelerate compute-intensive workloads — delivering 10 times higher performance than today’s fastest CPU.
Ian Buck, vice president of Accelerated Computing at NVIDIA, said: “With the addition of Tesla K80 GPUs, SoftLayer’s unique cloud offering for HPC will dramatically expand access to supercomputing-class performance, accelerating the pace of important new advances.”
