import time from tinygrad import Tensor, Device, GlobalCounters, TinyJit from tinygrad.ops import Ops, UOp from tinygrad.multi import MultiLazyBuffer, all_reduce from tinygrad.engine.schedule import create_schedule from tinygrad.engine.realize import run_schedule from tinygrad.helpers import getenv, Context, RING, DEBUG from typing import List, Union def realize(x: Union[UOp, List[UOp]]): x = x if isinstance(x, list) else [x] run_schedule(create_schedule(x)) for lb in x: Device[lb.device].synchronize() def test(devs: List[str], N: int, iters:int = 10): def _wrapped(op: Ops, t: Tensor) -> Tensor: return Tensor(MultiLazyBuffer(all_reduce(op, t.lazydata.lbs), 0), device=devs) _jitted = TinyJit(_wrapped) if getenv("USEJIT", 1) == 1 else _wrapped secs, gflops, gbs = 0, 0, 0 for i in range(-2, iters): lbs = [Tensor.full((N,), float(1+i), device=d).contiguous().lazydata for i,d in enumerate(devs)] realize(lbs) GlobalCounters.reset() start = time.time() realize(_jitted(Ops.ADD, Tensor(MultiLazyBuffer(lbs, 0), device=devs)).lazydata.lbs) if i < 0: continue # warm up jit i_secs = time.time() - start if DEBUG >= 2: i_secs = GlobalCounters.time_sum_s i_gflops = GlobalCounters.global_ops/i_secs/10**9 i_gbs = (N*4)/i_secs/10**9 print(f"{'ring_allreduce' if RING >= 2 else 'naive_allreduce'} iter {i+1}/{iters}: {i_secs:.6f} sec {i_gflops:.2f} GFLOP/s {i_gbs:.2f} GB/s") secs += i_secs gflops += i_gflops gbs += i_gbs return (gflops/iters, gbs/iters, secs/iters) def run(sz, n_gpus=6, iters=10): dev = Device.DEFAULT devs = tuple([f"{dev}:{x}" for x in range(n_gpus)]) N = sz // 4 # float32 is 4 bytes with Context(RING=2): (ring_gflops, ring_gbs, ring_secs) = test(devs, N, iters=iters) with Context(RING=0): (naive_gflops, naive_gbs, naive_secs) = test(devs, N, iters=iters) return (ring_gflops, ring_gbs, ring_secs), (naive_gflops, naive_gbs, naive_secs) def main(): n_gpus = getenv("GPUS", 6) if getenv("BENCHMARK_SPLIT"): l, r = 0, 512 while r - l > 1: m = (l + r) // 2 (ring_gflops, ring_gbs, ring_secs), (naive_gflops, naive_gbs, naive_secs) = run(m * 1024 * 4, n_gpus=n_gpus, iters=100) if ring_secs > naive_secs: l = m else: r = m print("Better split", r * 1024, "elements") else: sz = getenv("SZ", 1000) * 10**6 # size of data on each gpu print(f"Using {sz/10**9:.2f} GB of numbers on each of {n_gpus} GPUs, {n_gpus*sz/10**9:.2f} GB total.") (ring_gflops, ring_gbs, ring_secs), (naive_gflops, naive_gbs, naive_secs) = run(sz) print(f"Ring:\n {ring_secs:.6f} seconds/iter\n {ring_gflops:.2f} GFLOP/s\n {ring_gbs:.2f} GB/s") print(f"Naive:\n {naive_secs:.6f} seconds/iter\n {naive_gflops:.2f} GFLOP/s\n {naive_gbs:.2f} GB/s") if __name__ == "__main__": main()