def analyze_gemm_performance(m, n, k, operation="forward"):
    # Theoretical peak performance
    # H100 has ~1600 TFLOPS FP8 peak
    ops = 2 * m * n * k
    peak_time = ops / 1600e12  # Theoretical minimum time

    # Memory bandwidth
    fp8_bytes = (m * k + n * k) * 1  # FP8 inputs
    bf16_bytes = m * n * 2           # BF16 output  
    scale_bytes = ((m * k) // 128 + (n * k) // 128) * 4  # FP32 scales
    total_bytes = fp8_bytes + bf16_bytes + scale_bytes

    # H100 has ~3TB/s memory bandwidth
    bandwidth_time = total_bytes / 3e12

    print(f"\n{operation.upper()} GEMM Analysis (M={m}, N={n}, K={k}):")
    print(f"Operations: {ops/1e9:.1f} GigaOps")
    print(f"Compute bound time: {peak_time*1000:.2f}ms")
    print(f"Memory bound time: {bandwidth_time*1000:.2f}ms")
    print(f"Bottleneck: {'Compute' if peak_time > bandwidth_time else 'Memory'}")

# Analyze our configurations
analyze_gemm_performance(128, 256, 512, "forward")
analyze_gemm_performance(256, 512, 1024, "weight_grad")