HEAVY.AI Accelerates Big Data Analytics with Vultr’s High-Performance GPU Cloud Infrastructure

Partnership enables enterprises across core sectors such as energy, public sector, and telecommunications to achieve substantial speed improvements and cost savings

Vultr, the privately held cloud computing platform, announced a partnership with GPU-accelerated analytics platform provider HEAVY.AI. Integrating Vultr’s global NVIDIA GPU cloud infrastructure into its operations, HEAVY.AI can interactively query and visualize massive datasets, enabling faster, more efficient decision-making for customers across diverse sectors.

“Partnering with Vultr has allowed us to leverage their highly performant, global NVIDIA GPU cloud infrastructure to provide our customers with better access to unparalleled speed and efficiency,” said Jon Kondo, CEO of HEAVY.AI. “This integration ensures that our platform continues to deliver the rapid insights and cost savings that are critical for our customers’ success.”

Now, thanks to Vultr’s advanced GPU infrastructure, HEAVY.AI can deliver the best performance at an affordable price. The NVIDIA GH200 Grace Hopper™ Superchip joins NVIDIA A100 Tensor Core GPUs and Vultr Bare Metal instances to form a powerful trio that drives faster insights via the HEAVY.AI’s platform. With the NVIDIA GH200 running on Vultr Cloud, HEAVY.AI can deliver 5X or greater price performance when compared to 8XA100 instances, completing industry-standard analytic SQL benchmarks such as TPC-H100 in less than 4.5 seconds, and executing 11 of the 22 queries in less than 100 milliseconds.

“Vultr is one of the first cloud providers to offer the revolutionary NVIDIA GH200 Grace Hopper Superchip,” said Todd Mostak, Co-Founder and CTO of HEAVY.AI. “By tapping into the immense GPU compute and CPU-GPU bandwidth that is unique to the NVIDIA GH200, we now can offer our customers even greater performance and scale while significantly reducing costs, empowering businesses to derive insights faster and more efficiently than ever before.”

Building on its mission to democratize access to big data analytics, HEAVY.AI offers a comprehensive software suite that allows organizations to query, analyze, and visualize complex datasets, with a particular focus on location and time series data. With performance that is often orders of magnitude faster than CPU-based solutions, HEAVY.AI provides analysts, data scientists, data engineers, and geospatial professionals across industries with a complete view of their data, helping them understand the “what, when, and where” with unparalleled clarity. 

Through its collaborations with NVIDIA and now Vultr, HEAVY.AI has optimized its platform for the latest NVIDIA hardware to provide best-in-class performance, providing significant advantages to industries that rely on fast data processing. Specifically:

  • Energy: accelerating big data analytics for sectors such as renewable energy for wind, solar, biomass.
  • Telecommunications: expediting faster and deeper understanding of LTE and 5G networks, and enhancing customer experiences.
  • Urban planning & smart cities: accelerating the sector with GeoAI solutions, which analyze urban data to optimize infrastructure, transportation, and public services; and driving advanced utility analytics on big smart meter, IoT, and Earth observation datasets, for hidden risks visualization, and uninterrupted uptime.
  • Environmental monitoring, geospatial intelligence and disaster response: analyzing satellite and drone data to detect changes in land use; assessing damage from natural disasters faster; and automatic change detection and socio-economic analysis.

“As enterprises across sectors look to train and scale their models, they are looking for industry- and use case-specific solutions to help them accelerate growth and innovation,” said Kevin Cochrane, CMO of Vultr. “Our partnership with HEAVY.AI is yet another example of Vultr being committed to unlock the next frontier of GPU-accelerated analytics for some of the most data-intensive workloads across key sectors.”

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