Upscale AI Unveils SkyHammer Fabric to Challenge Nvidia’s Dominance in Scale-Up AI Networking

One of the most critical metrics for any scale-up fabric is how many accelerators it can support in a single memory domain. Nvidia’s current NVL72 rack-scale machine can glue together up to 72 GPUs, with the company aiming to scale its NVSwitch architecture to support 1,152 GPUs in the upcoming "Rubin Ultra" generation through multi-tier networking. Upscale AI’s SkyHammer architecture is entering this fray with the promise of supporting up to 576 accelerators in a single networking tier, with the ability to scale to "thousands" of devices across multiple tiers.

While the raw bandwidth per device on a 576-accelerator SkyHammer fabric—calculated at approximately 200 Gb/sec—is lower than the staggering 1.8 TB/sec offered by Nvidia’s NVSwitch 5/NVLink 5 generation, Upscale AI argues that bandwidth is only one part of the equation. For AI inference workloads in particular, the company contends that predictable latency and jitter are more important than peak theoretical throughput.

Arvind Srikumar, senior vice president of product and marketing at Upscale AI, emphasized that the SkyHammer ASIC was built from the ground up to handle the specific demands of AI. Traditional Ethernet fabrics often rely on fixed pipeline arrangements that lack the parallelism required for the most demanding AI models. In contrast, SkyFabriX incorporates mechanisms to ensure the fabric remains 100 percent lossless while maintaining a highly predictable latency profile. By starting with a "clean sheet" rather than retrofitting existing Ethernet protocols, Upscale AI believes it can offer a level of reliability that legacy systems struggle to match.

The Protocol War: UALink, ESUN, and the Ethernet Foundation

The battle for the scale-up market is also a battle of protocols. Currently, the industry is watching the development of UALink (Ultra Accelerator Link) and the associated UALoE (UALink over Ethernet) and ESUN memory protocols. These standards are being designed to run on top of fast Ethernet switches that have been specifically modified for scale-up tasks.

Interestingly, Upscale AI’s SkyHammer is designed to run UALoE and ESUN, confirming that, beneath its specialized features, SkyHammer is fundamentally an Ethernet switch ASIC. While some had hoped for a native UALink implementation with even higher radix, the decision to stick with an Ethernet-based foundation reflects the broader industry trend. Many experts, including the founders of Upscale AI, believe that Ethernet will eventually supersede InfiniBand as the dominant scale-out fabric for AI, especially as the Ultra Ethernet Consortium (UEC) finalizes its specifications.

While InfiniBand remains the gold standard for the absolute lowest port-to-port hop latency—a lead it has held for nearly three decades—Ethernet is closing the gap. More importantly, Ethernet offers superior scalability and a more robust ecosystem for the kind of massive, multi-tenant AI clusters being built by hyperscalers and cloud providers.

A Strategic Partnership with Nvidia