Chip Industry Week In Review


By Jesse Allen, Karen Heyman, and Liz Allan AMD took the covers off new AI accelerators for training and inferencing of large language model and high-performance computing workloads. In its announcement, AMD focused heavily on performance leadership in the commercial AI processor space through a combination of architectural changes, better software efficiency, along with some improvements in... » read more

Chip Industry Week In Review


By Jesse Allen, Karen Heyman, and Liz Allan Japan's Rapidus and the University of Tokyo are teaming up with France's Leti to meet its previously announced mass production goal of 2nm chips by 2027, and chips in the 1nm range in the 2030s. Rapidus was formed in 2022 with the support of eight Japanese companies — Sony, Kioxia, Denso, NEC, NTT, SoftBank, Toyota, and Mitsubishi's banking arm, ... » read more

Chip Industry Week In Review


By Jesse Allen, Gregory Haley, and Liz Allan Bosch, Infineon, and NXP were cleared in Germany to each acquire 10% of the European Semiconductor Manufacturing Co. (ESMC), established by TSMC, solidifying the supply chain against future shortages, particularly for automotive chips. “ESMC intends to build and operate another large semiconductor factory in Dresden, in which the three Europ... » read more

Chip Industry Week In Review


By Jesse Allen, Liz Allan, and Gregory Haley A potential government shutdown beginning in November would be "massively disruptive" for the Commerce Department as it continues to disburse critical funding featured in the CHIPS Act to boost semiconductor research and development in the U.S., according to Secretary Gina Raimondo. Global semiconductor industry sales totaled $44 billion in Aug... » read more

Chip Industry Week In Review


By Susan Rambo, Liz Allan, and Gregory Haley. TSMC rolled out the second version of its 3Dblox, which creates an infrastructure for stacking chiplets and other necessary components in a package, along with a standardized way of achieving that. Two novel features are chiplet mirroring for design reuse, and what is basically sandbox for power and thermal analysis of different design elements. ... » read more

Chip Industry Week In Review


By Liz Allan, Jesse Allen, and Karen Heyman Global semiconductor equipment billings dipped 2% year-over-year to US$25.8 billion in Q2, and slipped 4% compared with Q1, according to SEMI. Similarly, the top 10 semiconductor foundries reported a 1.1% quarterly-over-quarter revenue decline in Q2. A rebound is anticipated in Q3, according to TrendForce. Synopsys extended its AI-driven EDA ... » read more

Week In Review: Design, Low Power


Arm filed its registration statement for a highly anticipated IPO. Chip industry heavyweights Apple, Samsung, NVIDIA, and Intel are all expected to invest. Find the SEC filing here. Taiwan’s National Science and Technology Council (NSTC) laid out a 10-year initiative to bolster its IC design market share to 40% worldwide by 2033, with the first year’s budget of US $376 million. The sh... » read more

Week In Review: Design, Low Power


Qualcomm, NXP, Infineon, Nordic, and Bosch are jointly investing in a new RISC-V company, to be formed in Germany, that will speed up RISC-V’s adoption in commercial products. The company will be “a single source to enable compatible RISC-V based products, provide reference architectures, and help establish solutions widely used in the industry,” according to a press release. The co... » read more

Week In Review: Design, Low Power


Cadence rolled out a slew of new products at this week’s CDNLive Silicon Valley, including: A new generative AI-powered tool for analog, mixed-signal, RF and photonics design; An extended collaboration with TSMC and Microsoft to advance giga-scale physical verification system in the cloud; A multi-year partnership with the San Francisco 49ers football organization, focused on sust... » read more

Week In Review: Design, Low Power


MLCommons debuted the latest results for the MLPerf Inference v3.0 and Mobile v3.0 benchmark suites, which measure the performance and power-efficiency of applying a trained machine learning model to new data in data center, edge, and mobile use cases. Overall, MLCommons said the results showed both power efficiency improvements and significant gains in performance in some benchmark tests. Seve... » read more

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