[Hexagon] Add test demonstrating how to utilize a rolling buffer for avoiding repeated loads #13340

csullivan · 2022-11-10T00:09:24Z

This PR shows how to utilize the sch.rolling_buffer schedule primitive to avoid copying repeated rows when loading to fast memory. The example below is like conv2d with filter=[2, 1] and unit weights.

Before applying a rolling buffer to the height axis:

# from tvm.script import tir as T
@tvm.script.ir_module
class Module:
    @T.prim_func
    def main(A: T.Buffer[(6, 32), "float16"], B: T.Buffer[(5, 32), "float16"]):
        # function attr dict
        T.func_attr({"global_symbol": "main"})
        # body
        # with T.block("root")
        A_global_vtcm = T.alloc_buffer([6, 32], dtype="float16", scope="global.vtcm")
        for output_row in T.serial(5):
            for ax0, ax1 in T.grid(2, 32):
                with T.block("A_global.vtcm"):
                    v0 = T.axis.spatial(6, output_row + ax0)
                    v1 = T.axis.spatial(32, ax1)
                    T.reads(A[v0, v1])
                    T.writes(A_global_vtcm[v0, v1])
                    A_global_vtcm[v0, v1] = A[v0, v1]
            for i, rh in T.grid(32, 2):
                with T.block("compute"):
                    vrow, vi, vrh = T.axis.remap("SSR", [output_row, i, rh])
                    T.reads(A_global_vtcm[vrow + vrh, vi])
                    T.writes(B[vrow, vi])
                    with T.init():
                        B[vrow, vi] = T.cast(0, "float16")
                    B[vrow, vi] = B[vrow, vi] + A_global_vtcm[vrow + vrh, vi]

After applying sch.rolling_buffer to the cache_read block along the height axis:

# from tvm.script import tir as T
@tvm.script.ir_module
class Module:
    @T.prim_func
    def main(A: T.Buffer[(6, 32), "float16"], B: T.Buffer[(5, 32), "float16"]):
        # function attr dict
        T.func_attr({"global_symbol": "main"})
        # body
        # with T.block("root")
        A_global_vtcm = T.alloc_buffer([2, 32], dtype="float16", scope="global.vtcm")
        for output_row in T.serial(5):
            for ax0, ax1 in T.grid(2, 32):
                with T.block("A_global.vtcm"):
                    T.where(output_row < 1 or 1 <= ax0)
                    v0 = T.axis.opaque(6, output_row + ax0)
                    v1 = T.axis.spatial(32, ax1)
                    T.reads(A[v0, v1])
                    T.writes(A_global_vtcm[v0 % 2, v1])
                    A_global_vtcm[v0 % 2, v1] = A[v0, v1]
            for i, rh in T.grid(32, 2):
                with T.block("compute"):
                    vrow = T.axis.opaque(5, output_row)
                    vi, vrh = T.axis.remap("SR", [i, rh])
                    T.reads(A_global_vtcm[(vrow + vrh) % 2, vi])
                    T.writes(B[vrow, vi])
                    with T.init():
                        B[vrow, vi] = T.cast(0, "float16")
                    B[vrow, vi] = B[vrow, vi] + A_global_vtcm[(vrow + vrh) % 2, vi]

tvm-bot · 2022-11-10T00:09:28Z

Thanks for contributing to TVM! Please refer to the contributing guidelines https://tvm.apache.org/docs/contribute/ for useful information and tips. Please request code reviews from Reviewers by @-ing them in a comment.

Built docs for commit 2987911 can be found here.
cc @ibsidorenko _{See #10317 for details}

_{Generated by tvm-bot}

to avoid repeated loads on input rows needed by vertically output rows.

csullivan · 2022-11-10T04:55:42Z

cc @kparzysz-quic

Many thanks (!!) to @mbaret @NicolaLancellotti for the initial contribution of rolling buffer [1, 2], and to @liangW-intellif and @wrongtest-intellif for their recent translation of rolling buffer to a TIR schedule primitive [3], as well as all others involved in this work. It is a fantastic example of the benefit of a strong open source community!

mehrdadh

LGTM! just small changes

mehrdadh · 2022-11-10T17:32:50Z

tests/python/contrib/test_hexagon/test_rolling_buffer.py

+    return conv2d_2x1_filter
+
+
+def test_rolling_buffer_conv2d_2x1(hexagon_session):


Please add @tvm.testing.requires_hexagon

mehrdadh · 2022-11-10T17:33:12Z

tests/python/contrib/test_hexagon/test_rolling_buffer.py

+    a = tvm.nd.array(np.ones((6, 32), dtype=dtype), device=hexagon_session.device)
+    b = tvm.nd.array(np.zeros((5, 32), dtype=dtype), device=hexagon_session.device)
+    mod(a, b)
+    tvm.testing.assert_allclose(b.numpy(), np.full((5, 32), 2, dtype=dtype), atol=1e-3, rtol=1e-3)


Please add this to the end:

if __name__ == "__main__": tvm.testing.main()

csullivan · 2022-11-15T16:18:44Z

@tvm-bot rerun

masahi · 2022-11-28T08:46:02Z

@tvm-bot rerun

kparzysz-quic · 2023-01-09T17:40:43Z

@tvm-bot rerun

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Add test demonstrating how to utilize a rolling buffer

2987911

to avoid repeated loads on input rows needed by vertically output rows.

csullivan marked this pull request as ready for review November 10, 2022 04:55

masahi approved these changes Nov 10, 2022

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[Hexagon] Add test demonstrating how to utilize a rolling buffer for avoiding repeated loads #13340

[Hexagon] Add test demonstrating how to utilize a rolling buffer for avoiding repeated loads #13340

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		return conv2d_2x1_filter


		def test_rolling_buffer_conv2d_2x1(hexagon_session):

[Hexagon] Add test demonstrating how to utilize a rolling buffer for avoiding repeated loads #13340

[Hexagon] Add test demonstrating how to utilize a rolling buffer for avoiding repeated loads #13340

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csullivan commented Nov 10, 2022 •

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