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import torch
import time
import triton
import triton.language as tl
@triton.jit
def vortex_monolith_100x_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
x = tl.load(X + offsets, mask=mask)
# 100 FUSED OPS (Pure Register Persistence)
# This is how we break the 10x barrier
res = x
for _ in range(100):
res = res * 1.001 + 0.001
tl.store(Out + offsets, res, mask=mask)
def run_siege():
N = 1024 * 1024 * 128
print("--- BLITZ VORTEX: 100x FUSION SIEGE (H200) ---")
X = torch.randn(N, device="cuda")
Out = torch.empty_like(X)
# 1. Standard Way (100 Kernel Launches)
torch.cuda.synchronize()
start = time.time()
for _ in range(10):
curr = X
for _ in range(100): curr = curr * 1.001 + 0.001
torch.cuda.synchronize()
eager_ms = (time.time() - start) / 10 * 1000
# 2. Blitz Way (1 Monolith Launch)
grid = (triton.cdiv(N, 16384),)
torch.cuda.synchronize()
start = time.time()
for _ in range(10): vortex_monolith_100x_kernel[grid](X, Out, N, BLOCK_SIZE=16384)
torch.cuda.synchronize()
vortex_ms = (time.time() - start) / 10 * 1000
print(f"Eager Latency (100 passes): {eager_ms:.4f}ms")
print(f"Blitz Latency (1 pass): {vortex_ms:.4f}ms")
print(f"SILICON ART SPEEDUP: {eager_ms/vortex_ms:.2f}x")
if __name__ == "__main__":
run_siege()
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