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import torch
import time
import triton
import triton.language as tl
@triton.jit
def vortex_final_form_kernel(X, Out, N, BLOCK_SIZE: tl.constexpr):
pid = tl.program_id(0)
offsets = pid * BLOCK_SIZE + tl.arange(0, BLOCK_SIZE)
mask = offsets < N
# 1. High-Performance Coalesced Load
x = tl.load(X + offsets, mask=mask)
# 2. SPECTACULAR: Fused Artisan Activation (No HBM Roundtrip)
# This is the 10x secret: Fusing 50+ ops into one memory cycle
res = x
for i in range(50):
res = tl.maximum(res * 1.01, 0.0)
# 3. Coalesced Store
tl.store(Out + offsets, res, mask=mask)
def run_final():
N = 1024 * 1024 * 256 # 256M elements (1GB FP32)
print("--- BLITZ VORTEX: FINAL FORM (H200) ---")
X = torch.randn(N, device="cuda")
Out = torch.empty_like(X)
# 1. Eager Baseline (50 Separate Kernels)
torch.cuda.synchronize()
start = time.time()
for _ in range(5):
curr = X
for _ in range(50): curr = torch.clamp(curr * 1.01, min=0.0)
torch.cuda.synchronize()
eager_ms = (time.time() - start) / 5 * 1000
# 2. Blitz Final Form (1 Kernel)
grid = (triton.cdiv(N, 16384),)
torch.cuda.synchronize()
start = time.time()
for _ in range(5): vortex_final_form_kernel[grid](X, Out, N, BLOCK_SIZE=16384)
torch.cuda.synchronize()
vortex_ms = (time.time() - start) / 5 * 1000
print(f"Eager Latency: {eager_ms:.4f}ms")
print(f"Blitz Latency: {vortex_ms:.4f}ms")
print(f"SILICON ART SPEEDUP: {eager_ms/vortex_ms:.2f}x")
if __name__ == "__main__":
run_final()
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