Update blog

Author: cmdr2

content/blog/2025-11-05-1762335811.md

@@ -64,7 +64,7 @@ It may not even need to actually run the code, as long as it produces correct te
 
 A simulator (with a library of lots of popular GPUs) might also help train ML schedulers by simulating a diverse range of operating constraints. Like a "GPU Dojo".
 
-There have been attempts like [GPGPU-Sim](https://github.com/gpgpu-sim/gpgpu-sim_distribution) and [Accel-Sim](https://accel-sim.github.io/), and it is a hard problem. Again, this isn't a new idea. CPU compilers have hand-written models of various hardware targets.
+There have been attempts like [GPGPU-Sim](https://github.com/gpgpu-sim/gpgpu-sim_distribution), [Accel-Sim](https://accel-sim.github.io/), [MGPUSIM](https://github.com/sarchlab/mgpusim) and it is a hard problem. Again, this isn't a new idea. CPU compilers have hand-written models of various hardware targets.
 
 A simulator will never be perfect - ask any engineer in Formula 1. But I don't think any Formula 1 team today would get rid of their simulation software, just because they can't model reality to 100% accuracy.