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Microway, provider of computational clusters, servers and workstations for AI and HPC applications, announces it has provided an NVIDIA DGX-1 supercomputer and Microway NumberSmasher Tesla GPU Server to deep-learning leader Vyasa Analytics. The new hardware enables Vyasa Analytics’ next phase of growth.
The NVIDIA DGX-1 Deep Learning Appliance delivers performance for training neural networks and running production-scale classification workloads. The system leverages eight built-in NVIDIA Tesla V100 GPUs with NVIDIA NVLink Technology and Tensor Cores to boost the speed of deep learning training.
The system includes NVIDIA’s Deep Learning software stack and NGC containers. Immediately after installation, the system was ready to train models and scale Vyasa’s software. The easy-to-use DIGITS deep learning training system and interface available on DGX-1 helps users manage training data, monitor performance, and design, compare and select networks.
Microway’s NumberSmasher Tesla GPU Servers integrate 1–10 NVIDIA Tesla V100 GPUs with flexible GPU density. These servers are fully configurable for any customized workload. The Vyasa Analytics deployment utilized this configurability to deploy early R&D environments and test new concepts—scaled up onto the DGX-1 when ready.
Vyasa Analytics provides a deep learning analytics platform for organizations in the lbusiness intelligence verticals. Vyasa’s scalable deep learning software, Cortex, operating on NVIDIA GPUs and Microway server hardware, applies deep learning-based analytics to enterprise data of a variety of types: text, image and more. Use cases include analyzing multiple large-scale text sources and streams that include millions of documents in order to discover patterns, relationships, and trends.
“These systems have enabled us to branch out into a number of R&D areas that were really critical for us to be able to innovate and build out new types of deep learning approaches,” says Dr. Christopher Bouton, founder and CEO of Vyasa Analytics. “As a company working in the deep learning space, we see Microway and NVIDIA as key partners in our ability to build innovative novel deep learning algorithms for a wide range of content types.”
Microway experts architected, integrated, tested and installed the deployments.
Sources: Press materials received from the company and additional information gleaned from the company’s website.
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and…
Cut Retrieval-Augmented Generation (RAG) Hallucinations by 50%
Most teams hit the same wall with enterprise AI: LLMs that hallucinate, pipelines that don’t scale, and infrastructure that’s harder to design than the models themselves.
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