/*
 * Copyright 2019-2020 Marc Martos.  All rights reserved.
 */
//
//// System includes
//#include <iostream>
//#include <stdio.h>
//#include <assert.h>
//#include <math.h>
//
//// CUDA Runtime
//#include <cuda_runtime.h>
//
//// helper functions and utilities to work with CUDA
//#include <helper_functions.h>
//#include <helper_cuda.h>
//
//// Kernel function to add the elements of two arrays
//__global__
//void add(int n, float* x, float* y) {
//	int index = blockIdx.x * blockDim.x + threadIdx.x;
//	int stride = blockDim.x * gridDim.x;
//	for (int i = index; i < n; i += stride)
//		y[i] = x[i] + y[i];
//}
//
//__global__
//void calcError(int n, float* y, float* err) {
//	int index = blockIdx.x * blockDim.x + threadIdx.x;
//	int stride = blockDim.x * gridDim.x;
//	for (int i = index; i < n; i += stride)
//		*err = fmax(*err, fabs(y[i] - 3.0f));
//}
//
//int main(int argc, char** argv) {
//	const int N = 1 << 20;
//	float* x, * y;
//	float s_x[N], s_y[N];
//
//	// Allocate Unified Memory  accessible from CPU or GPU
//	cudaMallocManaged(&x, N * sizeof(float));
//	cudaMallocManaged(&y, N * sizeof(float));
//
//	// initialize x and y arrays on the host
//	for (int i = 0; i < N; i++) {
//		x[i] = 1.0f;
//		y[i] = 2.0f;
//	}
//	int blockSize = 256;
//	int numBlocks = (N + blockSize - 1) / blockSize;
//	// Run kernel on 1M elements on the GPU
//	//cudaMemcpy(x, s_x, N * sizeof(float), cudaMemcpyHostToDevice);
//	add <<< numBlocks , blockSize >>> (N, x, y);
//	//cudaMemcpy(s_x, x, N * sizeof(float), cudaMemcpyDeviceToHost);
//
//	// Wait for GPU to finish before accessing on host
//	cudaDeviceSynchronize();
//
//	// Check for errors (all values should be 3.0f)
//	float* maxError;
//
//	// Allocate Unified Memory  accessible from CPU or GPU
//	cudaMallocManaged(&maxError, sizeof(float));
//
//	// Run kernel on 1M elements on the GPU
//	calcError <<< 8, 1024 >> > (N, y, maxError);
//
//	// Wait for GPU to finish before accessing on host
//	cudaDeviceSynchronize();
//	
//	std::cout << "Max error: " << *maxError << std::endl;
//
//	// Free memory
//	cudaFree(x);
//	cudaFree(y);
//	cudaFree(maxError);
//
//	return EXIT_SUCCESS;
//}
	.file	"tmpxft_00376a2d_00000000-6_Add.cudafe1.cpp"
	.text
#APP

#NO_APP
	.type	_ZL26__cudaUnregisterBinaryUtilv, @function
_ZL26__cudaUnregisterBinaryUtilv:
.LFB2010:
	.cfi_startproc
	endbr64
	movq	_ZL20__cudaFatCubinHandle(%rip), %rdi
	jmp	__cudaUnregisterFatBinary@PLT
	.cfi_endproc
.LFE2010:
	.size	_ZL26__cudaUnregisterBinaryUtilv, .-_ZL26__cudaUnregisterBinaryUtilv
	.section	.text.startup,"ax",@progbits
	.type	_ZL24__sti____cudaRegisterAllv, @function
_ZL24__sti____cudaRegisterAllv:
.LFB2033:
	.cfi_startproc
	endbr64
	pushq	%rax
	.cfi_def_cfa_offset 16
	leaq	_ZL15__fatDeviceText(%rip), %rdi
	call	__cudaRegisterFatBinary@PLT
	movq	%rax, %rdi
	movq	%rax, _ZL20__cudaFatCubinHandle(%rip)
	call	__cudaRegisterFatBinaryEnd@PLT
	leaq	_ZL26__cudaUnregisterBinaryUtilv(%rip), %rdi
	popq	%rdx
	.cfi_def_cfa_offset 8
	jmp	atexit@PLT
	.cfi_endproc
.LFE2033:
	.size	_ZL24__sti____cudaRegisterAllv, .-_ZL24__sti____cudaRegisterAllv
	.section	.init_array,"aw"
	.align 8
	.quad	_ZL24__sti____cudaRegisterAllv
	.section	.nvFatBinSegment,"aw"
	.align 8
	.type	_ZL15__fatDeviceText, @object
	.size	_ZL15__fatDeviceText, 24
_ZL15__fatDeviceText:
	.long	1180844977
	.long	1
	.quad	fatbinData
	.quad	0
	.local	_ZL20__cudaFatCubinHandle
	.comm	_ZL20__cudaFatCubinHandle,8,8
	.ident	"GCC: (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0"
	.section	.note.GNU-stack,"",@progbits
	.section	.note.gnu.property,"a"
	.align 8
	.long	1f - 0f
	.long	4f - 1f
	.long	5
0:
	.string	"GNU"
1:
	.align 8
	.long	0xc0000002
	.long	3f - 2f
2:
	.long	0x3
3:
	.align 8
4:


#include <hip/hip_runtime.h>
/*
 * Copyright 2019-2020 Marc Martos.  All rights reserved.
 */
//
//// System includes
//#include <iostream>
//#include <stdio.h>
//#include <assert.h>
//#include <math.h>
//
//// CUDA Runtime
//#include <cuda_runtime.h>
//
//// helper functions and utilities to work with CUDA
//#include <helper_functions.h>
//#include <helper_cuda.h>
//
//// Kernel function to add the elements of two arrays
//__global__
//void add(int n, float* x, float* y) {
//	int index = blockIdx.x * blockDim.x + threadIdx.x;
//	int stride = blockDim.x * gridDim.x;
//	for (int i = index; i < n; i += stride)
//		y[i] = x[i] + y[i];
//}
//
//__global__
//void calcError(int n, float* y, float* err) {
//	int index = blockIdx.x * blockDim.x + threadIdx.x;
//	int stride = blockDim.x * gridDim.x;
//	for (int i = index; i < n; i += stride)
//		*err = fmax(*err, fabs(y[i] - 3.0f));
//}
//
//int main(int argc, char** argv) {
//	const int N = 1 << 20;
//	float* x, * y;
//	float s_x[N], s_y[N];
//
//	// Allocate Unified Memory  accessible from CPU or GPU
//	cudaMallocManaged(&x, N * sizeof(float));
//	cudaMallocManaged(&y, N * sizeof(float));
//
//	// initialize x and y arrays on the host
//	for (int i = 0; i < N; i++) {
//		x[i] = 1.0f;
//		y[i] = 2.0f;
//	}
//	int blockSize = 256;
//	int numBlocks = (N + blockSize - 1) / blockSize;
//	// Run kernel on 1M elements on the GPU
//	//cudaMemcpy(x, s_x, N * sizeof(float), cudaMemcpyHostToDevice);
//	add <<< numBlocks , blockSize >>> (N, x, y);
//	//cudaMemcpy(s_x, x, N * sizeof(float), cudaMemcpyDeviceToHost);
//
//	// Wait for GPU to finish before accessing on host
//	cudaDeviceSynchronize();
//
//	// Check for errors (all values should be 3.0f)
//	float* maxError;
//
//	// Allocate Unified Memory  accessible from CPU or GPU
//	cudaMallocManaged(&maxError, sizeof(float));
//
//	// Run kernel on 1M elements on the GPU
//	calcError <<< 8, 1024 >> > (N, y, maxError);
//
//	// Wait for GPU to finish before accessing on host
//	cudaDeviceSynchronize();
//	
//	std::cout << "Max error: " << *maxError << std::endl;
//
//	// Free memory
//	cudaFree(x);
//	cudaFree(y);
//	cudaFree(maxError);
//
//	return EXIT_SUCCESS;
//}
	.text
	.file	"Add.hip"
	.type	__hip_cuid_,@object             # @__hip_cuid_
	.bss
	.globl	__hip_cuid_
__hip_cuid_:
	.byte	0                               # 0x0
	.size	__hip_cuid_, 1

	.ident	"AMD clang version 18.0.0git (https://github.com/RadeonOpenCompute/llvm-project roc-6.3.2 25012 e5bf7e55c91490b07c49d8960fa7983d864936c4)"
	.section	".note.GNU-stack","",@progbits
	.addrsig
	.addrsig_sym __hip_cuid_

	.text
	.p2alignl 7, 3214868480
	.fill 96, 4, 3214868480
	.type	__hip_cuid_,@object             ; @__hip_cuid_
	.section	.bss,"aw",@nobits
	.globl	__hip_cuid_
__hip_cuid_:
	.byte	0                               ; 0x0
	.size	__hip_cuid_, 1

	.ident	"AMD clang version 18.0.0git (https://github.com/RadeonOpenCompute/llvm-project roc-6.3.2 25012 e5bf7e55c91490b07c49d8960fa7983d864936c4)"
	.section	".note.GNU-stack","",@progbits
	.addrsig
	.addrsig_sym __hip_cuid_
	.amdgcn_target "amdgcn-amd-amdhsa--gfx1100"
	.amdgpu_metadata
---
amdhsa.kernels:  []
amdhsa.target:   amdgcn-amd-amdhsa--gfx1100
amdhsa.version:
  - 1
  - 2
...

	.end_amdgpu_metadata
