The current Triton implementation for FP8 quantization and matrix multiplication operations can be significantly optimized for better performance and memory efficiency. Key issues include suboptimal memory access patterns, redundant calculations, and inefficient autotuning configurations.

Optimized code with improvements in:

Memory access patterns for better cache utilization
Computation efficiency with reduced redundant operations
Refined autotuning configurations focusing on common scenarios

kernel.py

The optimized version maintains identical functional behavior while improving performance through:
Optimized memory loading with proper masking
Improved amax calculation and scaling logic
Streamlined autotuning configurations
More efficient pointer arithmetic and loop structures