Released by
Shi-Xin Zhang, Institute of Physics, CAS
Contact email
shixinzhang@iphy.ac.cn
Method
Quantum Circuit Simulation
Challenge issue
Extreme-efficiency VQE numerical simulation
Goal
Build an iteratable, auto-evaluatable harness framework that uses semi-automated algorithm–engineering co-innovation to achieve a VQE computation scheme surpassing the current tensorcircuit-ng official baseline in both space efficiency and time efficiency (including first-time JIT compilation efficiency and subsequent runtime execution efficiency).
More ambitiously, the harness framework should automatically and reliably help users optimize TensorCircuit-NG-based code scripts for performance.
Optimization dimensions (reference pool)
Algorithm level:
- Tensor network contraction path search
- Slicing search
Engineering level:
scan control flow
- AOT compilation
- Operator fusion and customization
- Automatic differentiation checkpointing
- Memory offloading
- Mixed precision
Released by
Shi-Xin Zhang, Institute of Physics, CAS
Contact email
shixinzhang@iphy.ac.cn
Method
Quantum Circuit Simulation
Challenge issue
Extreme-efficiency VQE numerical simulation
Goal
Build an iteratable, auto-evaluatable harness framework that uses semi-automated algorithm–engineering co-innovation to achieve a VQE computation scheme surpassing the current
tensorcircuit-ngofficial baseline in both space efficiency and time efficiency (including first-time JIT compilation efficiency and subsequent runtime execution efficiency).More ambitiously, the harness framework should automatically and reliably help users optimize TensorCircuit-NG-based code scripts for performance.
Optimization dimensions (reference pool)
Algorithm level:
Engineering level:
scancontrol flow