gevico/cosim-gpu

An execution-driven, cycle-accurate GPU simulator for modern architectures and AI workloads.

This is the top-level repository for the Accel-Sim framework.

A highly-flexible GPU simulator for AMD GPUs.

GPGPU-Sim provides a detailed simulation model of contemporary NVIDIA GPUs running CUDA and/or OpenCL workloads. It includes support for features such as TensorCores and CUDA Dynamic Parallelism as well as a performance visualization tool, AerialVisoin, and an integrated energy model, GPUWattch.

A Heterogeneous GPU Platform for AI and Neural Graphics

A lightweight Python-based GPU architecture simulator that demonstrates how parallel threads, registers, memory, and instructions work on a GPU.

A Python framework for GPU-accelerated simulation, robotics, and machine learning.

Sionna Research Kit: A GPU-Accelerated Research Platform for AI-RAN

Qwen3.5-2B with a SIMT GPU inside its weights, 45 compiled layers in front of Qwen’s own, using its Gated DeltaNet layers as registers and memory.