Slice update with operation (#3266)

2026-03-18 06:18:02 -07:00
parent e353be8235
commit 7bc61cceed
18 changed files with 1475 additions and 184 deletions
@@ -0,0 +1,109 @@
+# Copyright © 2023-2024 Apple Inc.
+
+import argparse
+
+import mlx.core as mx
+import torch
+from time_utils import measure_runtime
+
+
+def benchmark_slice_update_mlx(dst_shape, slice_shape, slice_range, dtype, iters=10):
+    def slice_update(arguments):
+        for i in range(iters):
+            arguments["dst"] = (
+                arguments["dst"].at[slice_range].add(arguments["updates"])
+            )
+        mx.eval(arguments)
+
+    dtype = getattr(mx, dtype)
+    arguments = {
+        "dst": mx.random.normal(dst_shape).astype(dtype),
+        "updates": mx.random.normal(slice_shape).astype(dtype),
+    }
+
+    runtime = measure_runtime(slice_update, arguments=arguments)
+    bytes_processed = (
+        arguments["dst"][slice_range].nbytes * 2 + arguments["updates"].nbytes
+    ) * iters
+    bandwidth_gb_s = bytes_processed / runtime / 1e6
+    return runtime, bandwidth_gb_s
+
+
+def benchmark_slice_update_torch(
+    dst_shape, slice_shape, slice_range, device, dtype, iters=10
+):
+    def slice_update(dst, updates, slice_range):
+        for i in range(iters):
+            dst[slice_range] = dst[slice_range] + updates
+        if device == torch.device("mps"):
+            torch.mps.synchronize()
+
+    dtype = getattr(torch, dtype)
+    updates = torch.randn(slice_shape, dtype=dtype).to(device)
+    dst = torch.randn(dst_shape, dtype=dtype).to(device)
+
+    runtime = measure_runtime(
+        slice_update, dst=dst, updates=updates, slice_range=slice_range
+    )
+    bytes_processed = (dst[slice_range].nbytes * 2 + updates.nbytes) * iters
+    bandwidth_gb_s = bytes_processed / runtime / 1e6
+    return runtime, bandwidth_gb_s
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser("Slice update benchmarks.")
+    parser.add_argument("--cpu", action="store_true", help="Use the CPU.")
+    args = parser.parse_args()
+
+    if args.cpu:
+        mx.set_default_device(mx.cpu)
+        device = torch.device("cpu")
+    elif torch.mps.is_available():
+        device = torch.device("mps")
+    elif torch.cuda.is_available():
+        device = torch.device("cuda")
+    else:
+        raise ValueError()
+
+    dtypes = ["float32", "bfloat16"]
+
+    test_cases = [
+        ((10_000_000,), slice(0, 1_000_000), (1_000_000,)),
+        ((100_000,), slice(10_000, 20_000), (10_000,)),
+        ((1000, 64), slice(100, 200), (100, 64)),
+        ((100, 100, 64), slice(20, 40), (20, 100, 64)),
+        (
+            (2048, 2048, 128),
+            (slice(500, 1500), slice(200, 1200), slice(32, 96)),
+            (1000, 1000, 64),
+        ),
+        (
+            (2048, 2048, 128),
+            (slice(1800, 1850), slice(100, 200), slice(64, 128)),
+            (50, 100, 64),
+        ),
+        (
+            (2048, 2048, 128),
+            (slice(1000, 1010), slice(1000, 1010), slice(64, 128)),
+            (10, 10, 64),
+        ),
+    ]
+
+    print(
+        f"{'Dtype':<12} {'Dst Shape':<25} {'Update Shape':<20} "
+        f"{'MLX (ms)':<12} {'MLX GB/s':<12} {'Torch (ms)':<12} {'Torch GB/s':<12}"
+    )
+    print("-" * 110)
+
+    for dtype in dtypes:
+        for dst_shape, slice_range, update_shape in test_cases:
+            mlx_time, mlx_bw = benchmark_slice_update_mlx(
+                dst_shape, update_shape, slice_range, dtype
+            )
+            torch_time, torch_bw = benchmark_slice_update_torch(
+                dst_shape, update_shape, slice_range, device, dtype
+            )
+            print(
+                f"{dtype:<12} {str(dst_shape):<25} {str(update_shape):<20} "
+                f"{mlx_time:<12.3f} {mlx_bw:<12.2f} {torch_time:<12.3f} {torch_bw:<12.2f}"
+            )