; Copyright (c) 2014-2023, NVIDIA CORPORATION. All rights reserved.
;
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;  * Redistributions of source code must retain the above copyright
;    notice, this list of conditions and the following disclaimer.
;  * Redistributions in binary form must reproduce the above copyright
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;  * Neither the name of NVIDIA CORPORATION nor the names of its
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;
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; This NVVM IR program shows how to use shared memory.
; What it does is similar to the following CUDA C code.
;
;
; __shared__ int a;
; __shared__ int b[10];
;
; __global__ void foo()
; {
;   a = 1;
;   b[5] = 2;
; }
;

target datalayout = "e-p:64:64:64-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:64:64-i128:128:128-f32:32:32-f64:64:64-v16:16:16-v32:32:32-v64:64:64-v128:128:128-n16:32:64"
target triple = "nvptx64-nvidia-cuda"

@a = internal addrspace(3) global i32 undef, align 4
@b = internal addrspace(3) global [10 x i32] undef, align 4

define void @foo() {
entry:
  store i32 1, i32 addrspace(3)* @a, align 4
  store i32 2, i32 addrspace(3)* getelementptr inbounds ([10 x i32], [10 x i32] addrspace(3)* @b, i64 0, i64 5), align 4
  ret void
}

!nvvm.annotations = !{!0}
!0 = !{void ()* @foo, !"kernel", i32 1}

!nvvmir.version = !{!1}
!1 = !{i32 2, i32 0}