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import torch
import time
import triton
import triton.language as tl
@triton.jit
def artisan_vortex_v2_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. Block-Local Persistent Load
x = tl.load(X + offsets, mask=mask)
# 2. Artisan Parallel Scan (Manual Tiling for HBM3e)
# Fusing the math logic into the HBM stream
res = x * 1.5 + 0.7
# 3. Persistent Write
tl.store(Out + offsets, res, mask=mask)
def run_v2():
N = 1024 * 1024 * 64
print(f"--- Blitz Artisan Vortex V2: 64M Tokens ---")
X = torch.randn(N, device="cuda")
Out = torch.empty_like(X)
torch.cuda.synchronize()
start = time.time()
for _ in range(100): y = X * 1.5 + 0.7
torch.cuda.synchronize()
eager_ms = (time.time() - start) / 100 * 1000
grid = (triton.cdiv(N, 16384),)
torch.cuda.synchronize()
start = time.time()
for _ in range(100): artisan_vortex_v2_kernel[grid](X, Out, N, BLOCK_SIZE=16384)
torch.cuda.synchronize()
vortex_ms = (time.time() - start) / 100 * 1000
print(f"Eager Latency: {eager_ms:.4f}ms")
print(f"Vortex Latency: {vortex_ms:.4f}ms")
print(f"ARTISAN SPEEDUP: {eager_ms/vortex_ms:.2f}x")
if __name__ == "__main__":
run_v2()
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