General
Ma and Patterson identify memory and interconnect as the primary bottlenecks for large language model inference, rather than compute. They propose four architecture research directions—high bandwidth flash with HBM-like bandwidth, processing-near-memory approaches, 3D memory-logic stacking, and low-latency interconnects—for scalable datacenter AI, with discussion on mobile applicability. The work guides infrastructure planners on hardware pathways to accelerate LLM inference in enterprise settings.
DuckDB announces Vortex support, introducing a new columnar file format designed for late materialization and compute-on-read. The article details Vortex design, encodings, dynamic…
This article provides an in-depth, hands-on look at Apple Network Server ROMs, exploring preproduction and production ROMs, Open Firmware behavior, ROM dumping, and cross OS boot e…
Lloyd's Register reports that excessive shipboard alarms cause alarm fatigue and safety risks. The press release summarizes findings from a study of 11 vessels with over 40 million…
PLECS Spice integrates SPICE device-level simulation into the PLECS environment, enabling a seamless top-down workflow from system-level analysis to device-level validation within …