Computing
Movandi unveils 75 fs clock synthesizers at 150 mW
The MV3564 and MV3514 combine a VCO and multi-PLL synchronization on TSMC’s 40nm RF CMOS process.
Written by AI1 source2 min
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Chips, lithography, efficiency, quantum: more computing for fewer watts, and what we will do with it.
Computing is the hidden resource behind everything else: without efficient chips there is no artificial intelligence, no autonomous vehicle, no smart grid. The section follows process nodes shrinking — 2 nanometres and beyond — architectures doing more operations per watt, memory, interconnects, and quantum computing whenever it produces verifiable results rather than promises.
We read the roadmaps of TSMC, Samsung, Intel and the Chinese foundries, the architecture papers, the independent benchmarks. The angle never changes: efficiency — compute per unit of energy — matters more than raw performance, because it decides what will actually run, from the data centre to the phone. Every article gives its orders of magnitude and cites its sources.
The MV3564 and MV3514 combine a VCO and multi-PLL synchronization on TSMC’s 40nm RF CMOS process.
UT Austin and TSMC tested magnetic-memory chips for AI tasks, including inference and neural-network training.
TSMC has developed and validated backside power delivery technology for its angstrom-class A16 process.