With the down-scaling of CMOS technology, the design complexity of very large-scale
integrated is increasing. Although the application of machine learning (ML) techniques in …

It has been a long time that computer architecture and systems are optimized for efficient
execution of machine learning (ML) models. Now, it is time to reconsider the relationship …

Chip floorplanning is the engineering task of designing the physical layout of a computer
chip. Despite five decades of research, chip floorplanning has defied automation, requiring …

Placement is a critical step in modern chip design, aiming to determine the positions of
circuit modules on the chip canvas. Recent works have shown that reinforcement learning …

Placement for very-large-scale integrated (VLSI) circuits is one of the most important steps
for design closure. This paper proposes a novel GPU-accelerated placement framework …

Placement is an essential task in modern chip design, aiming at placing millions of circuit
modules on a 2D chip canvas. Unlike the human-centric solution, which requires months of …

Fast and accurate pre-routing timing prediction is essential for timing-driven placement since
repetitive routing and static timing analysis (STA) iterations are expensive and …

We describe the planned Alpha release of OpenROAD, an open-source end-to-end silicon
compiler. OpenROAD will help realize the goal of" democratization of hardware design", by …

For its advantage in GPU acceleration and less dependency on human experts, machine
learning has been an emerging tool for solving the placement and routing problems, as two …

Macro placement is a critical very large-scale integration (VLSI) physical design problem
that significantly impacts the design power-performance-area (PPA) metrics. This paper …