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Articles tagged with "Semiconductors, AI, Hardware"

SemiEngineering

Chip Industry Technical Paper Roundup: Apr. 21

New technical papers in the semiconductor industry cover topics such as neural computers, AFM on EUV nanostructures, photonic chip packaging for extreme environments, SSD emulation for GPU-centric storage, ruthenium interconnects, DRAM power delivery, silent data corruption, LLM training reliability, GPU Rowhammer, and privilege escalation. Researchers from various organizations like Meta AI, KAUST, Purdue University, Intel, NIST, Johns Hopkins, and UT Austin have contributed to these papers.

SemiEngineering•
SemiEngineering

Chip Industry Technical Paper Roundup: Jan 12

The article discusses various technical papers recently added to Semiconductor Engineering's library, covering topics such as challenges and research directions for large language model inference hardware by Google, aging-aware steepening of fault coverage in scan-based transition fault tests by Purdue University, cryogenic ultra-thin body SiGeSn transistors, physical AI at the edge by Arizona State University, neuromorphic hardware, 2.5D flip-chip packages with thermal-mechanical optimization, gradient electronic landscapes in van der Waals heterostructures, and acoustic side-channel attacks. These papers delve into cutting-edge advancements in the chip industry, exploring innovative hardware solutions and research directions.

SemiEngineering•
Semiconductor industry enters unprecedented ‘giga cycle’, says report — scale of artificial intelligence is rewriting compute, memory, networking, and storage economics all at once

Semiconductor industry enters unprecedented ‘giga cycle’, says report — scale of artificial intelligence is rewriting compute, memory, networking, and storage economics all at once

The semiconductor industry is experiencing an unprecedented "giga cycle" driven by the scale of artificial intelligence (AI) demand, which is reshaping the economics of compute, memory, networking, and storage. Forecasts indicate that the semiconductor market could surpass the trillion-dollar mark by 2028 or 2029, with AI playing a significant role in this growth. Companies like AMD and Nvidia are raising long-term expectations, with projections of a $1 trillion AI hardware market by 2030. The AI infrastructure opportunity is estimated to be between $3 trillion to $4 trillion in the coming years, leading to significant growth in data-processing silicon and AI accelerators. This shift is also driving increased demand for custom silicon, memory, and packaging technologies.

Tom's Hardware•

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