Abbrevation
GLSVLSI
City
Beijing, China
Country
United States
Deadline Paper
Start Date
End Date
Abstract

The 30th edition of GLSVLSI will be held in Beijing, China. Original, unpublished papers describing research in the general areas of VLSI and hardware design are solicited. Please visit http://www.glsvlsi.org/ for more information. In addition to the traditional topic areas of GLSVLSI listed below, papers are solicited for a special theme of “In-Memory Processing for future electronics”. Program Tracks: • VLSI Design: ASIC and FPGA design, microprocessors/micro-architectures, embedded processors, analog/digital/mixed-signal systems, NoC, SoC, IoT, interconnects, memories, bioinspired and neuromorphic circuits and systems, BioMEMs, lab-on-a-chip, biosensors, CAD tools for biology and biomedical systems, implantable and wearable devices. • VLSI Circuits and Power Aware Design: analog/digital/mixed-signal circuits, RF and communication circuits, chaos/neural/fuzzy-logic circuits, high-speed/low-power circuits, temperature estimation/optimization, power estimation/optimization. • Computer-Aided Design (CAD): hardware/software co-design, high-level synthesis, logic synthesis, simulation and formal verification, layout, design for manufacturing, algorithms and complexity analysis. • Testing, Reliability, Fault-Tolerance: digital/analog/mixed-signal testing, reliability, robustness, static and dynamic defect- and fault-recoverability, variation-aware design. • Emerging Computing & Post-CMOS Technologies: nanotechnology, quantum computing, approximate and stochastic computing, sensor and sensor networks, post CMOS VLSI. • Hardware Security: trusted IC, IP protection, hardware security primitives, reverse engineering, hardware Trojan, side-channel analysis, CPS and IoT security. • VLSI for Machine Learning and Artificial Intelligence: hardware accelerators for machine learning, novel architectures for deep learning, brain-inspired computing, big data computing, reinforcement learning, cloud computing for Internet-of-Things (IoT) devices. • Microelectronic Systems Education: Pedagogical innovations using a wide range of technologies such as ASIC, FPGA, multicore, GPU, educational techniques including novel curricula and laboratories, assessment methods, distance learning, textbooks, and design projects, Industry and academic collaborative programs and teaching.