Students have one more compelling reason to study computing at Georgia Tech: they now have access to work on a state-of-the-art supercomputer.
The NVIDIA DGX-1 supercomputer is a specialty graphics processing unit (GPU)-based platform designed to facilitate faster and more efficient big data sequencing, machine learning (ML), and deep learning processes.
“There aren’t many computers or servers significant enough to be recognizable by model name. But, a DGX-1 is well-known throughout the computing community, particularly by the artificial intelligence and machine learning crowd,” said School of Computational Science and Engineering (CSE) Research Technologist Will Powell.
Still images showing the DGX-1 supercomputer placed inside a computer tower at the College of Computing Data Center. The first image shows the computer with the front cover and the second shows the computer with the front cover removed.
Although the DGX-1 is a well-known system, these high-profile computers are not normally accessible to the broader computational science community because of their cost, which is why this opportunity is unique for Georgia Tech students.
CSE won funding for the DGX-1 as part of a bid approved in this fiscal year’s campus Technology Fee Funding. This institute-level program is orchestrated by a committee comprised of faculty, staff, and students that review proposals from across campus to purchase various technologies for instruction and learning.
“CSE strives to cultivate a diverse computing environment with ground-breaking technologies, such as the DGX-1. Providing students with the opportunity to use and study best-in-class, forward-thinking architectures allows us to further pioneer new computational methods,” said Powell.
The DGX-1 will become available for the Fall 2019 semester in the data and visual analytics classes (CX4242 and CSE6242) taught by Lecturer Mahdi Roozbahani and Associate Professor Polo Chau. Students in these classes will use this platform to accelerate computational analysis performed on large-scale real-world datasets.
“This is a great opportunity for students to have access to a high performance platform designed for artificial intelligence, ML, deep learning, and analytics,” said Joint CSE and NVIDIA Senior Graph Software Engineer Oded Green, whose research focuses on improving the performance and scalability of large-scale graph analytics using platforms such as the DGX-1.
The DGX-1 is powered by 8 NVIDIA TESLA V100 GPUs, has over 40,000 CUDA Cores, 5,000 Tensor cores, and 1,000 TFLOPS built specially for deep learning.
And while the DGX-1 arriving at Georgia Tech for student-use is exciting enough, there is cause for more celebration as a DGX Station also arrived this year as part of the new NVIDIA Artificial Intelligence (AI) Lab (NVAIL) grant awarded to CSE.
The NVAIL grant focuses on developing multi-GPU graph analytics and the DGX station is constructed specifically for data science and artificial intelligence development. The station will be used for graduate students and researchers associated with the NVAIL.