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LESSON

A5 — GPU-accelerated placement optimization

Software environment: gcc7.5.0, g++7.5.0, glibc2.27, python3.7, cuda-driver.

1. Problem background

iPL mainly uses nonlinear gradient optimization algorithm, which can be accelerated by GPU.

2. Problem description

2.1 Description

2.2 Problem case

2.3 Output requirements

2.4 Competition environment

(1) Operating environment

  • Operating system: linux system;

  • Hardware environment: 64-bit x86 CPU, 128GB running memory, 1TB hard drive, NVIDIA-GPU;

  • Software environment: gcc7.5.0, g++7.5.0, glibc2.27, python3.7, cuda-driver.

(2) Reference tools

iPL:https://gitee.com/oscc-project/iEDAopen in new window