BDx Data Centers Achieves NVIDIA DGX-Ready Certification
BDx Data Centers has been certified in the NVIDIA DGX-Ready Data Center program, as announced in a press release. This certification applies to BDx's 500MW CGK4 AI Campus in Indonesia, marking it as one of the first in the country to achieve this status. The certification enables BDx to provide scalable and high-performance infrastructure for AI and advanced computing workloads.
The CGK4 AI Campus offers interconnected colocation facilities and edge sites, facilitating NVIDIA accelerated computing for training and inferencing at the edge. This infrastructure supports the development of full-stack AI solutions while ensuring data localization and meeting the demands of AI-driven innovation.
BDx's commitment to sustainability is evident as the CGK4 AI Campus is Indonesia's first renewable-powered AI data center park. The facility also integrates direct-to-chip liquid cooling at scale, an industry-first in Indonesia, enhancing energy efficiency for high-density AI computing. BDx aims to expand its capacity to 1 GW, supporting the region's growing digital economy and AI-driven applications.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Silicon Brief or Daily AI Brief.
Also, consider following us on social media:
More from Data Centers
Nov 1 SpaceX AI Loses Bid to Dismiss NAACP Air Pollution Lawsuit Oct 31 Canada Joins EuroHPC Supercomputing and Quantum Network Oct 31 Anthropic IPO Filing Details Nearly $900 Billion in Future Obligations Oct 31 IBS Agrees to Acquire AI Chip Company for HK$563 Million Oct 30 Perplexity Signs Multi-Year Deal for Blackwell Ultra GPUs on IREN AI CloudSilicon Brief
Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
GreenSquareDC Opens Sydney AI Data Center With 8,200 NVIDIA GPUs
DayOne Supports NVIDIA DSX POD Data Center Design
Cortex DC Plans 2 GW of Data Center Capacity in India
Brightray Signs Letter of Intent for 10 MW Indiana AI Data Center
OneQode Signs 14 MW AI Capacity Deal in Chennai
Daily AI Brief: the AI news that matters, in your inbox.