
namespace fastertransformer {

const unsigned int WARP_REDUCE_MASK = 0xffffffff;
const float CUDA_FLOAT_INF_NEG = -100000000.f;
const unsigned int WARP_SIZE = 32;

template <typename T>
__forceinline__ __device__ T warpReduceMax(T val) {
  for (int mask = (WARP_SIZE >> 1); mask > 0; mask >>= 1)
    val = max(val, __shfl_xor_sync(WARP_REDUCE_MASK, val, mask, WARP_SIZE));
  return val;
}


/* Calculate the maximum of all elements in a block */
template <typename T>
__forceinline__ __device__ T blockReduceMax(T val) {
  static __shared__ T shared[32];
  int lane = threadIdx.x & 0x1f;
  int wid = threadIdx.x >> 5;

  val = warpReduceMax<T>(val);

  if (lane == 0) shared[wid] = val;
  __syncthreads();

  val = (threadIdx.x < ((blockDim.x + 31) >> 5)) ? shared[lane]
                                                 : CUDA_FLOAT_INF_NEG;
  val = warpReduceMax<T>(val);
  return val;
}

/* Calculate the rough topk-th value in a block, rough but safe */
template <typename T, int K>
__forceinline__ __device__ T blockRoughTopK(T val) {
  static __shared__ T shared[32];
  int lane = threadIdx.x & 0x1f;
  int wid = threadIdx.x >> 5;
  val = warpReduceMax(val);

  if (lane == 0) shared[wid] = val;
  __syncthreads();

  // we do not care about result of threadIdx.x bigger than (blockDim.x >> 5)
  val = (threadIdx.x < (blockDim.x >> 5)) ? shared[lane] : CUDA_FLOAT_INF_NEG;

  // K should be 2, 4, 6, 8, 16 or 32
  for (int mask = 16; mask >= K; mask >>= 1)
    val = max(val, __shfl_xor_sync(WARP_REDUCE_MASK, val, mask, 32));
  for (int mask = (K >> 1); mask > 0; mask >>= 1)
    val = min(val, __shfl_xor_sync(WARP_REDUCE_MASK, val, mask, 32));

  return val;
}
}
	.file	"tmpxft_0022213f_00000000-6_lightseq_kernels.cudafe1.cpp"
	.text
#APP

#NO_APP
	.type	_ZL26__cudaUnregisterBinaryUtilv, @function
_ZL26__cudaUnregisterBinaryUtilv:
.LFB2013:
	.cfi_startproc
	endbr64
	movq	_ZL20__cudaFatCubinHandle(%rip), %rdi
	jmp	__cudaUnregisterFatBinary@PLT
	.cfi_endproc
.LFE2013:
	.size	_ZL26__cudaUnregisterBinaryUtilv, .-_ZL26__cudaUnregisterBinaryUtilv
	.section	.text.startup,"ax",@progbits
	.type	_ZL24__sti____cudaRegisterAllv, @function
_ZL24__sti____cudaRegisterAllv:
.LFB2036:
	.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
.LFE2036:
	.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>

namespace fastertransformer {

const unsigned int WARP_REDUCE_MASK = 0xffffffff;
const float CUDA_FLOAT_INF_NEG = -100000000.f;
const unsigned int WARP_SIZE = 32;

template <typename T>
__forceinline__ __device__ T warpReduceMax(T val) {
  for (int mask = (WARP_SIZE >> 1); mask > 0; mask >>= 1)
    val = max(val, __shfl_xor_sync(WARP_REDUCE_MASK, val, mask, WARP_SIZE));
  return val;
}


/* Calculate the maximum of all elements in a block */
template <typename T>
__forceinline__ __device__ T blockReduceMax(T val) {
  static __shared__ T shared[32];
  int lane = threadIdx.x & 0x1f;
  int wid = threadIdx.x >> 5;

  val = warpReduceMax<T>(val);

  if (lane == 0) shared[wid] = val;
  __syncthreads();

  val = (threadIdx.x < ((blockDim.x + 31) >> 5)) ? shared[lane]
                                                 : CUDA_FLOAT_INF_NEG;
  val = warpReduceMax<T>(val);
  return val;
}

/* Calculate the rough topk-th value in a block, rough but safe */
template <typename T, int K>
__forceinline__ __device__ T blockRoughTopK(T val) {
  static __shared__ T shared[32];
  int lane = threadIdx.x & 0x1f;
  int wid = threadIdx.x >> 5;
  val = warpReduceMax(val);

  if (lane == 0) shared[wid] = val;
  __syncthreads();

  // we do not care about result of threadIdx.x bigger than (blockDim.x >> 5)
  val = (threadIdx.x < (blockDim.x >> 5)) ? shared[lane] : CUDA_FLOAT_INF_NEG;

  // K should be 2, 4, 6, 8, 16 or 32
  for (int mask = 16; mask >= K; mask >>= 1)
    val = max(val, __shfl_xor_sync(WARP_REDUCE_MASK, val, mask, 32));
  for (int mask = (K >> 1); mask > 0; mask >>= 1)
    val = min(val, __shfl_xor_sync(WARP_REDUCE_MASK, val, mask, 32));

  return val;
}
}
	.text
	.file	"lightseq_kernels.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
