On-die monitors, localized analytics, and lifecycle data are giving architects new ways to close the gap between design ...
NVMe on-controller memory; SSN datapaths; Git-based chip workflows; low-light image enhancement; testing AI networks.
When is a complex chip design ready to be shipped to manufacturing?
Researchers from Google and University of California, Berkeley published a technical paper titled “Google’s Training ...
Researchers from University of Wisconsin-Madison and AMD Research and Advanced Development published a technical paper titled ...
Researchers from Seoul National University, Stanford University, and Chinese Academy of Sciences developed an ...
Standalone GPUs are being replaced by heterogeneous SoCs and chiplets that combine CPUs, GPUs, and NPUs to eliminate memory ...
Yu Ma. As AI-driven workloads continue to push the boundaries of compute scale, power efficiency, and bandwidth density, ...
The verification gap emerges not from a lack of computational power but from the multiphysics nature of 3D-IC behavior.
A new architecture enables higher data rates and densities while remaining pin-compatible with traditional DIMM.
As AI models drive compute demand, servers keep getting bigger. Rack‑scale AI systems (such as the 72-GPU systems from NVIDIA or AMD) enable many GPUs to work together through system-level ...
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