Accelerating Engineering with Blackwell Hardware

Synopsys and NVIDIA Reveal Agentic AI Workflows

Collaboration at GTC 2026 targets silicon-to-systems engineering with Blackwell-accelerated performance gains.

By Kronos Digital News Desk··1 min read
A stylized digital illustration of a semiconductor wafer integrated with glowing neural network connections in a dark data center setting.

A stylized digital illustration of a semiconductor wafer integrated with glowing neural network connections in a dark data center setting.

Photo: Kronos Digital News

Synopsys and NVIDIA announced a strategic partnership at the GTC 2026 conference to build a hardware-accelerated agentic AI stack [1]. This system focuses on silicon-to-systems engineering to streamline complex electronic design workflows [1][2]. The collaboration leverages advanced computing to improve efficiency across the semiconductor industry [3]. The demonstration showed 30X speedups in quantum chemistry tasks using NVIDIA’s new Blackwell hardware [1][2]. Engineers also reported significantly faster circuit simulation times during the presentation [2]. These tools help teams manage the increasing complexity of modern system-on-chip designs [1][3].

Editorial notes

Transparency note

Drafted with LLM; human-edited

AI assisted
Yes
Human review
Yes
Last updated

Risk assessment

Under review

Reviewed for sourcing quality and editorial consistency.

Sources

Related stories

View all

Topics

Get the weekly briefing

A concise briefing with selected stories and analysis.

No spam. Unsubscribe anytime. By joining, you agree to our Privacy Policy.

About the author

Kronos Digital News Desk covers accelerating engineering with blackwell hardware and editorial analysis for Kronos Digital News.