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ðŸ“ ..
ðŸ“„ __clang_cuda_builtin_vars.h(4.78 KB)
ðŸ“„ __clang_cuda_cmath.h(18.06 KB)
ðŸ“„ __clang_cuda_complex_builtins.h(9.36 KB)
ðŸ“„ __clang_cuda_device_functions.h(56.68 KB)
ðŸ“„ __clang_cuda_intrinsics.h(29.93 KB)
ðŸ“„ __clang_cuda_libdevice_declares.h(21.87 KB)
ðŸ“„ __clang_cuda_math.h(15.99 KB)
ðŸ“„ __clang_cuda_math_forward_declares.h(8.27 KB)
ðŸ“„ __clang_cuda_runtime_wrapper.h(17.61 KB)
ðŸ“„ __clang_cuda_texture_intrinsics.h(31.86 KB)
ðŸ“„ __clang_hip_cmath.h(26.34 KB)
ðŸ“„ __clang_hip_libdevice_declares.h(19.87 KB)
ðŸ“„ __clang_hip_math.h(31.96 KB)
ðŸ“„ __clang_hip_runtime_wrapper.h(4.65 KB)
ðŸ“„ __clang_hip_stdlib.h(1.19 KB)
ðŸ“„ __stddef_max_align_t.h(857 B)
ðŸ“„ __wmmintrin_aes.h(5.15 KB)
ðŸ“„ __wmmintrin_pclmul.h(1.99 KB)
ðŸ“„ adxintrin.h(7.37 KB)
ðŸ“„ altivec.h(697.32 KB)
ðŸ“„ ammintrin.h(7.54 KB)
ðŸ“„ amxcomplexintrin.h(6.81 KB)
ðŸ“„ amxfp16intrin.h(1.82 KB)
ðŸ“„ amxintrin.h(21.12 KB)
ðŸ“„ arm64intr.h(993 B)
ðŸ“„ arm_acle.h(25.66 KB)
ðŸ“„ arm_bf16.h(548 B)
ðŸ“„ arm_cde.h(32.67 KB)
ðŸ“„ arm_cmse.h(6.21 KB)
ðŸ“„ arm_fp16.h(16.92 KB)
ðŸ“„ arm_mve.h(1.48 MB)
ðŸ“„ arm_neon.h(2.45 MB)
ðŸ“„ arm_neon_sve_bridge.h(9.48 KB)
ðŸ“„ arm_sme_draft_spec_subject_to_change.h(60.2 KB)
ðŸ“„ arm_sve.h(1.51 MB)
ðŸ“„ armintr.h(843 B)
ðŸ“„ avx2intrin.h(186.96 KB)
ðŸ“„ avx512bf16intrin.h(10.51 KB)
ðŸ“„ avx512bitalgintrin.h(2.41 KB)
ðŸ“„ avx512bwintrin.h(75.33 KB)
ðŸ“„ avx512cdintrin.h(4.12 KB)
ðŸ“„ avx512dqintrin.h(58.75 KB)
ðŸ“„ avx512erintrin.h(11.83 KB)
ðŸ“„ avx512fintrin.h(382.64 KB)
ðŸ“„ avx512fp16intrin.h(156.63 KB)
ðŸ“„ avx512ifmaintrin.h(2.49 KB)
ðŸ“„ avx512ifmavlintrin.h(4.31 KB)
ðŸ“„ avx512pfintrin.h(4.53 KB)
ðŸ“„ avx512vbmi2intrin.h(13.17 KB)
ðŸ“„ avx512vbmiintrin.h(3.72 KB)
ðŸ“„ avx512vbmivlintrin.h(6.94 KB)
ðŸ“„ avx512vlbf16intrin.h(19.21 KB)
ðŸ“„ avx512vlbitalgintrin.h(4.23 KB)
ðŸ“„ avx512vlbwintrin.h(121.26 KB)
ðŸ“„ avx512vlcdintrin.h(7.66 KB)
ðŸ“„ avx512vldqintrin.h(46.41 KB)
ðŸ“„ avx512vlfp16intrin.h(85.51 KB)
ðŸ“„ avx512vlintrin.h(322.29 KB)
ðŸ“„ avx512vlvbmi2intrin.h(25.72 KB)
ðŸ“„ avx512vlvnniintrin.h(13.13 KB)
ðŸ“„ avx512vlvp2intersectintrin.h(4.44 KB)
ðŸ“„ avx512vnniintrin.h(4.21 KB)
ðŸ“„ avx512vp2intersectintrin.h(2.9 KB)
ðŸ“„ avx512vpopcntdqintrin.h(2 KB)
ðŸ“„ avx512vpopcntdqvlintrin.h(3.31 KB)
ðŸ“„ avxifmaintrin.h(5.75 KB)
ðŸ“„ avxintrin.h(195.41 KB)
ðŸ“„ avxneconvertintrin.h(14.09 KB)
ðŸ“„ avxvnniint16intrin.h(17.41 KB)
ðŸ“„ avxvnniint8intrin.h(18.67 KB)
ðŸ“„ avxvnniintrin.h(10.44 KB)
ðŸ“„ bmi2intrin.h(7.09 KB)
ðŸ“„ bmiintrin.h(14.12 KB)
ðŸ“„ builtins.h(741 B)
ðŸ“„ cet.h(1.49 KB)
ðŸ“„ cetintrin.h(3.27 KB)
ðŸ“„ cldemoteintrin.h(1.18 KB)
ðŸ“„ clflushoptintrin.h(1.17 KB)
ðŸ“„ clwbintrin.h(1.2 KB)
ðŸ“„ clzerointrin.h(1.19 KB)
ðŸ“„ cmpccxaddintrin.h(2.33 KB)
ðŸ“„ cpuid.h(11.01 KB)
ðŸ“„ crc32intrin.h(3.27 KB)
ðŸ“ cuda_wrappers
ðŸ“„ emmintrin.h(192.64 KB)
ðŸ“„ enqcmdintrin.h(2.12 KB)
ðŸ“„ f16cintrin.h(5.39 KB)
ðŸ“„ float.h(5.63 KB)
ðŸ“„ fma4intrin.h(6.82 KB)
ðŸ“„ fmaintrin.h(28.4 KB)
ðŸ“„ fxsrintrin.h(2.82 KB)
ðŸ“„ gfniintrin.h(7.57 KB)
ðŸ“„ hexagon_circ_brev_intrinsics.h(15.59 KB)
ðŸ“„ hexagon_protos.h(374.42 KB)
ðŸ“„ hexagon_types.h(130.33 KB)
ðŸ“„ hresetintrin.h(1.36 KB)
ðŸ“„ htmintrin.h(6.14 KB)
ðŸ“„ htmxlintrin.h(9.01 KB)
ðŸ“„ hvx_hexagon_protos.h(254.26 KB)
ðŸ“„ ia32intrin.h(12.72 KB)
ðŸ“„ immintrin.h(23.57 KB)
ðŸ“„ intrin.h(28.22 KB)
ðŸ“„ inttypes.h(2.26 KB)
ðŸ“„ invpcidintrin.h(764 B)
ðŸ“„ iso646.h(656 B)
ðŸ“„ keylockerintrin.h(17.98 KB)
ðŸ“„ larchintrin.h(7.8 KB)
ðŸ“„ limits.h(3.61 KB)
ðŸ“ llvm_libc_wrappers
ðŸ“„ lwpintrin.h(5 KB)
ðŸ“„ lzcntintrin.h(3.18 KB)
ðŸ“„ mm3dnow.h(4.5 KB)
ðŸ“„ mm_malloc.h(1.88 KB)
ðŸ“„ mmintrin.h(55.98 KB)
ðŸ“„ module.modulemap(3.33 KB)
ðŸ“„ movdirintrin.h(1.57 KB)
ðŸ“„ msa.h(25.01 KB)
ðŸ“„ mwaitxintrin.h(2.19 KB)
ðŸ“„ nmmintrin.h(709 B)
ðŸ“„ opencl-c-base.h(30.38 KB)
ðŸ“„ opencl-c.h(874.39 KB)
ðŸ“ openmp_wrappers
ðŸ“„ pconfigintrin.h(1.19 KB)
ðŸ“„ pkuintrin.h(934 B)
ðŸ“„ pmmintrin.h(10.5 KB)
ðŸ“„ popcntintrin.h(1.82 KB)
ðŸ“ ppc_wrappers
ðŸ“„ prfchiintrin.h(2.02 KB)
ðŸ“„ prfchwintrin.h(2.06 KB)
ðŸ“„ ptwriteintrin.h(1.05 KB)
ðŸ“„ raointintrin.h(6.59 KB)
ðŸ“„ rdpruintrin.h(1.59 KB)
ðŸ“„ rdseedintrin.h(2.85 KB)
ðŸ“„ riscv_ntlh.h(855 B)
ðŸ“„ rtmintrin.h(1.25 KB)
ðŸ“„ s390intrin.h(604 B)
ðŸ“„ serializeintrin.h(881 B)
ðŸ“„ sgxintrin.h(1.77 KB)
ðŸ“„ sha512intrin.h(5.95 KB)
ðŸ“„ shaintrin.h(7.37 KB)
ðŸ“„ sifive_vector.h(522 B)
ðŸ“„ sm3intrin.h(7.29 KB)
ðŸ“„ sm4intrin.h(8.2 KB)
ðŸ“„ smmintrin.h(99.32 KB)
ðŸ“„ stdalign.h(911 B)
ðŸ“„ stdarg.h(1.66 KB)
ðŸ“„ stdatomic.h(8.3 KB)
ðŸ“„ stdbool.h(1.04 KB)
ðŸ“„ stddef.h(4.16 KB)
ðŸ“„ stdint.h(32.49 KB)
ðŸ“„ stdnoreturn.h(1.17 KB)
ðŸ“„ tbmintrin.h(3.15 KB)
ðŸ“„ tgmath.h(29.68 KB)
ðŸ“„ tmmintrin.h(29.51 KB)
ðŸ“„ tsxldtrkintrin.h(1.97 KB)
ðŸ“„ uintrintrin.h(4.96 KB)
ðŸ“„ unwind.h(11.21 KB)
ðŸ“„ vadefs.h(1.39 KB)
ðŸ“„ vaesintrin.h(2.46 KB)
ðŸ“„ varargs.h(477 B)
ðŸ“„ vecintrin.h(360.82 KB)
ðŸ“„ velintrin.h(2.1 KB)
ðŸ“„ velintrin_approx.h(3.54 KB)
ðŸ“„ velintrin_gen.h(69.06 KB)
ðŸ“„ vpclmulqdqintrin.h(1.06 KB)
ðŸ“„ waitpkgintrin.h(1.33 KB)
ðŸ“„ wasm_simd128.h(76.25 KB)
ðŸ“„ wbnoinvdintrin.h(749 B)
ðŸ“„ wmmintrin.h(659 B)
ðŸ“„ x86gprintrin.h(2.32 KB)
ðŸ“„ x86intrin.h(1.81 KB)
ðŸ“„ xmmintrin.h(106.73 KB)
ðŸ“„ xopintrin.h(19.96 KB)
ðŸ“„ xsavecintrin.h(2.51 KB)
ðŸ“„ xsaveintrin.h(1.64 KB)
ðŸ“„ xsaveoptintrin.h(1 KB)
ðŸ“„ xsavesintrin.h(1.24 KB)
ðŸ“„ xtestintrin.h(873 B)

Editing: __clang_cuda_runtime_wrapper.h

/*===---- __clang_cuda_runtime_wrapper.h - CUDA runtime support -------------===
 *
 * Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
 * See https://llvm.org/LICENSE.txt for license information.
 * SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 *
 *===-----------------------------------------------------------------------===
 */

/*
 * WARNING: This header is intended to be directly -include'd by
 * the compiler and is not supposed to be included by users.
 *
 * CUDA headers are implemented in a way that currently makes it
 * impossible for user code to #include directly when compiling with
 * Clang. They present different view of CUDA-supplied functions
 * depending on where in NVCC's compilation pipeline the headers are
 * included. Neither of these modes provides function definitions with
 * correct attributes, so we use preprocessor to force the headers
 * into a form that Clang can use.
 *
 * Similarly to NVCC which -include's cuda_runtime.h, Clang -include's
 * this file during every CUDA compilation.
 */

#ifndef __CLANG_CUDA_RUNTIME_WRAPPER_H__
#define __CLANG_CUDA_RUNTIME_WRAPPER_H__

#if defined(__CUDA__) && defined(__clang__)

// Include some forward declares that must come before cmath.
#include <__clang_cuda_math_forward_declares.h>

// Define __CUDACC__ early as libstdc++ standard headers with GNU extensions
// enabled depend on it to avoid using __float128, which is unsupported in
// CUDA.
#define __CUDACC__

// Include some standard headers to avoid CUDA headers including them
// while some required macros (like __THROW) are in a weird state.
#include <cmath>
#include <cstdlib>
#include <stdlib.h>
#include <string.h>
#undef __CUDACC__

// Preserve common macros that will be changed below by us or by CUDA
// headers.
#pragma push_macro("__THROW")
#pragma push_macro("__CUDA_ARCH__")

// WARNING: Preprocessor hacks below are based on specific details of
// CUDA-7.x headers and are not expected to work with any other
// version of CUDA headers.
#include "cuda.h"
#if !defined(CUDA_VERSION)
#error "cuda.h did not define CUDA_VERSION"
#elif CUDA_VERSION < 7000
#error "Unsupported CUDA version!"
#endif

#pragma push_macro("__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__")
#if CUDA_VERSION >= 10000
#define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__
#endif

// Make largest subset of device functions available during host
// compilation.
#ifndef __CUDA_ARCH__
#define __CUDA_ARCH__ 9999
#endif

#include "__clang_cuda_builtin_vars.h"

// No need for device_launch_parameters.h as __clang_cuda_builtin_vars.h above
// has taken care of builtin variables declared in the file.
#define __DEVICE_LAUNCH_PARAMETERS_H__

// {math,device}_functions.h only have declarations of the
// functions. We don't need them as we're going to pull in their
// definitions from .hpp files.
#define __DEVICE_FUNCTIONS_H__
#define __MATH_FUNCTIONS_H__
#define __COMMON_FUNCTIONS_H__
// device_functions_decls is replaced by __clang_cuda_device_functions.h
// included below.
#define __DEVICE_FUNCTIONS_DECLS_H__

#undef __CUDACC__
#if CUDA_VERSION < 9000
#define __CUDABE__
#else
#define __CUDACC__
#define __CUDA_LIBDEVICE__
#endif
// Disables definitions of device-side runtime support stubs in
// cuda_device_runtime_api.h
#include "host_defines.h"
#undef __CUDACC__
#include "driver_types.h"
#include "host_config.h"

// Temporarily replace "nv_weak" with weak, so __attribute__((nv_weak)) in
// cuda_device_runtime_api.h ends up being __attribute__((weak)) which is the
// functional equivalent of what we need.
#pragma push_macro("nv_weak")
#define nv_weak weak
#undef __CUDABE__
#undef __CUDA_LIBDEVICE__
#define __CUDACC__
#include "cuda_runtime.h"

#pragma pop_macro("nv_weak")
#undef __CUDACC__
#define __CUDABE__

// CUDA headers use __nvvm_memcpy and __nvvm_memset which Clang does
// not have at the moment. Emulate them with a builtin memcpy/memset.
#define __nvvm_memcpy(s, d, n, a) __builtin_memcpy(s, d, n)
#define __nvvm_memset(d, c, n, a) __builtin_memset(d, c, n)

#if CUDA_VERSION < 9000
#include "crt/device_runtime.h"
#endif
#include "crt/host_runtime.h"
// device_runtime.h defines __cxa_* macros that will conflict with
// cxxabi.h.
// FIXME: redefine these as __device__ functions.
#undef __cxa_vec_ctor
#undef __cxa_vec_cctor
#undef __cxa_vec_dtor
#undef __cxa_vec_new
#undef __cxa_vec_new2
#undef __cxa_vec_new3
#undef __cxa_vec_delete2
#undef __cxa_vec_delete
#undef __cxa_vec_delete3
#undef __cxa_pure_virtual

// math_functions.hpp expects this host function be defined on MacOS, but it
// ends up not being there because of the games we play here.  Just define it
// ourselves; it's simple enough.
#ifdef __APPLE__
inline __host__ double __signbitd(double x) {
  return std::signbit(x);
}
#endif

// CUDA 9.1 no longer provides declarations for libdevice functions, so we need
// to provide our own.
#include <__clang_cuda_libdevice_declares.h>

// Wrappers for many device-side standard library functions, incl. math
// functions, became compiler builtins in CUDA-9 and have been removed from the
// CUDA headers. Clang now provides its own implementation of the wrappers.
#if CUDA_VERSION >= 9000
#include <__clang_cuda_device_functions.h>
#include <__clang_cuda_math.h>
#endif

// __THROW is redefined to be empty by device_functions_decls.h in CUDA. Clang's
// counterpart does not do it, so we need to make it empty here to keep
// following CUDA includes happy.
#undef __THROW
#define __THROW

// CUDA 8.0.41 relies on __USE_FAST_MATH__ and __CUDA_PREC_DIV's values.
// Previous versions used to check whether they are defined or not.
// CU_DEVICE_INVALID macro is only defined in 8.0.41, so we use it
// here to detect the switch.

#if defined(CU_DEVICE_INVALID)
#if !defined(__USE_FAST_MATH__)
#define __USE_FAST_MATH__ 0
#endif

#if !defined(__CUDA_PREC_DIV)
#define __CUDA_PREC_DIV 0
#endif
#endif

// Temporarily poison __host__ macro to ensure it's not used by any of
// the headers we're about to include.
#pragma push_macro("__host__")
#define __host__ UNEXPECTED_HOST_ATTRIBUTE

// device_functions.hpp and math_functions*.hpp use 'static
// __forceinline__' (with no __device__) for definitions of device
// functions. Temporarily redefine __forceinline__ to include
// __device__.
#pragma push_macro("__forceinline__")
#define __forceinline__ __device__ __inline__ __attribute__((always_inline))
#if CUDA_VERSION < 9000
#include "device_functions.hpp"
#endif

// math_function.hpp uses the __USE_FAST_MATH__ macro to determine whether we
// get the slow-but-accurate or fast-but-inaccurate versions of functions like
// sin and exp.  This is controlled in clang by -fcuda-approx-transcendentals.
//
// device_functions.hpp uses __USE_FAST_MATH__ for a different purpose (fast vs.
// slow divides), so we need to scope our define carefully here.
#pragma push_macro("__USE_FAST_MATH__")
#if defined(__CLANG_CUDA_APPROX_TRANSCENDENTALS__)
#define __USE_FAST_MATH__ 1
#endif

#if CUDA_VERSION >= 9000
#include "crt/math_functions.hpp"
#else
#include "math_functions.hpp"
#endif

#pragma pop_macro("__USE_FAST_MATH__")

#if CUDA_VERSION < 9000
#include "math_functions_dbl_ptx3.hpp"
#endif
#pragma pop_macro("__forceinline__")

// Pull in host-only functions that are only available when neither
// __CUDACC__ nor __CUDABE__ are defined.
#undef __MATH_FUNCTIONS_HPP__
#undef __CUDABE__
#if CUDA_VERSION < 9000
#include "math_functions.hpp"
#endif
// Alas, additional overloads for these functions are hard to get to.
// Considering that we only need these overloads for a few functions,
// we can provide them here.
static inline float rsqrt(float __a) { return rsqrtf(__a); }
static inline float rcbrt(float __a) { return rcbrtf(__a); }
static inline float sinpi(float __a) { return sinpif(__a); }
static inline float cospi(float __a) { return cospif(__a); }
static inline void sincospi(float __a, float *__b, float *__c) {
  return sincospif(__a, __b, __c);
}
static inline float erfcinv(float __a) { return erfcinvf(__a); }
static inline float normcdfinv(float __a) { return normcdfinvf(__a); }
static inline float normcdf(float __a) { return normcdff(__a); }
static inline float erfcx(float __a) { return erfcxf(__a); }

#if CUDA_VERSION < 9000
// For some reason single-argument variant is not always declared by
// CUDA headers. Alas, device_functions.hpp included below needs it.
static inline __device__ void __brkpt(int __c) { __brkpt(); }
#endif

// Now include *.hpp with definitions of various GPU functions.  Alas,
// a lot of thins get declared/defined with __host__ attribute which
// we don't want and we have to define it out. We also have to include
// {device,math}_functions.hpp again in order to extract the other
// branch of #if/else inside.
#define __host__
#undef __CUDABE__
#define __CUDACC__
#if CUDA_VERSION >= 9000
// Some atomic functions became compiler builtins in CUDA-9 , so we need their
// declarations.
#include "device_atomic_functions.h"
#endif
#undef __DEVICE_FUNCTIONS_HPP__
#include "device_atomic_functions.hpp"
#if CUDA_VERSION >= 9000
#include "crt/device_functions.hpp"
#include "crt/device_double_functions.hpp"
#else
#include "device_functions.hpp"
#define __CUDABE__
#include "device_double_functions.h"
#undef __CUDABE__
#endif
#include "sm_20_atomic_functions.hpp"
// Predicate functions used in `__builtin_assume` need to have no side effect.
// However, sm_20_intrinsics.hpp doesn't define them with neither pure nor
// const attribute. Rename definitions from sm_20_intrinsics.hpp and re-define
// them as pure ones.
#pragma push_macro("__isGlobal")
#pragma push_macro("__isShared")
#pragma push_macro("__isConstant")
#pragma push_macro("__isLocal")
#define __isGlobal __ignored_cuda___isGlobal
#define __isShared __ignored_cuda___isShared
#define __isConstant __ignored_cuda___isConstant
#define __isLocal __ignored_cuda___isLocal
#include "sm_20_intrinsics.hpp"
#pragma pop_macro("__isGlobal")
#pragma pop_macro("__isShared")
#pragma pop_macro("__isConstant")
#pragma pop_macro("__isLocal")
#pragma push_macro("__DEVICE__")
#define __DEVICE__ static __device__ __forceinline__ __attribute__((const))
__DEVICE__ unsigned int __isGlobal(const void *p) {
  return __nvvm_isspacep_global(p);
}
__DEVICE__ unsigned int __isShared(const void *p) {
  return __nvvm_isspacep_shared(p);
}
__DEVICE__ unsigned int __isConstant(const void *p) {
  return __nvvm_isspacep_const(p);
}
__DEVICE__ unsigned int __isLocal(const void *p) {
  return __nvvm_isspacep_local(p);
}
#pragma pop_macro("__DEVICE__")
#include "sm_32_atomic_functions.hpp"

// Don't include sm_30_intrinsics.h and sm_32_intrinsics.h.  These define the
// __shfl and __ldg intrinsics using inline (volatile) asm, but we want to
// define them using builtins so that the optimizer can reason about and across
// these instructions.  In particular, using intrinsics for ldg gets us the
// [addr+imm] addressing mode, which, although it doesn't actually exist in the
// hardware, seems to generate faster machine code because ptxas can more easily
// reason about our code.

#if CUDA_VERSION >= 8000
#pragma push_macro("__CUDA_ARCH__")
#undef __CUDA_ARCH__
#include "sm_60_atomic_functions.hpp"
#include "sm_61_intrinsics.hpp"
#pragma pop_macro("__CUDA_ARCH__")
#endif

#undef __MATH_FUNCTIONS_HPP__

// math_functions.hpp defines ::signbit as a __host__ __device__ function.  This
// conflicts with libstdc++'s constexpr ::signbit, so we have to rename
// math_function.hpp's ::signbit.  It's guarded by #undef signbit, but that's
// conditional on __GNUC__.  :)
#pragma push_macro("signbit")
#pragma push_macro("__GNUC__")
#undef __GNUC__
#define signbit __ignored_cuda_signbit

// CUDA-9 omits device-side definitions of some math functions if it sees
// include guard from math.h wrapper from libstdc++. We have to undo the header
// guard temporarily to get the definitions we need.
#pragma push_macro("_GLIBCXX_MATH_H")
#pragma push_macro("_LIBCPP_VERSION")
#if CUDA_VERSION >= 9000
#undef _GLIBCXX_MATH_H
// We also need to undo another guard that checks for libc++ 3.8+
#ifdef _LIBCPP_VERSION
#define _LIBCPP_VERSION 3700
#endif
#endif

#if CUDA_VERSION >= 9000
#include "crt/math_functions.hpp"
#else
#include "math_functions.hpp"
#endif
#pragma pop_macro("_GLIBCXX_MATH_H")
#pragma pop_macro("_LIBCPP_VERSION")
#pragma pop_macro("__GNUC__")
#pragma pop_macro("signbit")

#pragma pop_macro("__host__")

// __clang_cuda_texture_intrinsics.h must be included first in order to provide
// implementation for __nv_tex_surf_handler that CUDA's headers depend on.
// The implementation requires c++11 and only works with CUDA-9 or newer.
#if __cplusplus >= 201103L && CUDA_VERSION >= 9000
// clang-format off
#include <__clang_cuda_texture_intrinsics.h>
// clang-format on
#else
#if CUDA_VERSION >= 9000
// Provide a hint that texture support needs C++11.
template <typename T> struct __nv_tex_needs_cxx11 {
  const static bool value = false;
};
template <class T>
__host__ __device__ void __nv_tex_surf_handler(const char *name, T *ptr,
                                               cudaTextureObject_t obj,
                                               float x) {
  _Static_assert(__nv_tex_needs_cxx11<T>::value,
                 "Texture support requires C++11");
}
#else
// Textures in CUDA-8 and older are not supported by clang.There's no
// convenient way to intercept texture use in these versions, so we can't
// produce a meaningful error. The source code that attempts to use textures
// will continue to fail as it does now.
#endif // CUDA_VERSION
#endif // __cplusplus >= 201103L && CUDA_VERSION >= 9000
#include "texture_fetch_functions.h"
#include "texture_indirect_functions.h"

// Restore state of __CUDA_ARCH__ and __THROW we had on entry.
#pragma pop_macro("__CUDA_ARCH__")
#pragma pop_macro("__THROW")

// Set up compiler macros expected to be seen during compilation.
#undef __CUDABE__
#define __CUDACC__

extern "C" {
// Device-side CUDA system calls.
// http://docs.nvidia.com/cuda/ptx-writers-guide-to-interoperability/index.html#system-calls
// We need these declarations and wrappers for device-side
// malloc/free/printf calls to work without relying on
// -fcuda-disable-target-call-checks option.
__device__ int vprintf(const char *, const char *);
__device__ void free(void *) __attribute((nothrow));
__device__ void *malloc(size_t) __attribute((nothrow)) __attribute__((malloc));

// __assertfail() used to have a `noreturn` attribute. Unfortunately that
// contributed to triggering the longstanding bug in ptxas when assert was used
// in sufficiently convoluted code. See
// https://bugs.llvm.org/show_bug.cgi?id=27738 for the details.
__device__ void __assertfail(const char *__message, const char *__file,
                             unsigned __line, const char *__function,
                             size_t __charSize);

// In order for standard assert() macro on linux to work we need to
// provide device-side __assert_fail()
__device__ static inline void __assert_fail(const char *__message,
                                            const char *__file, unsigned __line,
                                            const char *__function) {
  __assertfail(__message, __file, __line, __function, sizeof(char));
}

// Clang will convert printf into vprintf, but we still need
// device-side declaration for it.
__device__ int printf(const char *, ...);
} // extern "C"

// We also need device-side std::malloc and std::free.
namespace std {
__device__ static inline void free(void *__ptr) { ::free(__ptr); }
__device__ static inline void *malloc(size_t __size) {
  return ::malloc(__size);
}
} // namespace std

// Out-of-line implementations from __clang_cuda_builtin_vars.h.  These need to
// come after we've pulled in the definition of uint3 and dim3.

__device__ inline __cuda_builtin_threadIdx_t::operator dim3() const {
  return dim3(x, y, z);
}

__device__ inline __cuda_builtin_threadIdx_t::operator uint3() const {
  return {x, y, z};
}

__device__ inline __cuda_builtin_blockIdx_t::operator dim3() const {
  return dim3(x, y, z);
}

__device__ inline __cuda_builtin_blockIdx_t::operator uint3() const {
  return {x, y, z};
}

__device__ inline __cuda_builtin_blockDim_t::operator dim3() const {
  return dim3(x, y, z);
}

__device__ inline __cuda_builtin_blockDim_t::operator uint3() const {
  return {x, y, z};
}

__device__ inline __cuda_builtin_gridDim_t::operator dim3() const {
  return dim3(x, y, z);
}

__device__ inline __cuda_builtin_gridDim_t::operator uint3() const {
  return {x, y, z};
}

#include <__clang_cuda_cmath.h>
#include <__clang_cuda_intrinsics.h>
#include <__clang_cuda_complex_builtins.h>

// curand_mtgp32_kernel helpfully redeclares blockDim and threadIdx in host
// mode, giving them their "proper" types of dim3 and uint3.  This is
// incompatible with the types we give in __clang_cuda_builtin_vars.h.  As as
// hack, force-include the header (nvcc doesn't include it by default) but
// redefine dim3 and uint3 to our builtin types.  (Thankfully dim3 and uint3 are
// only used here for the redeclarations of blockDim and threadIdx.)
#pragma push_macro("dim3")
#pragma push_macro("uint3")
#define dim3 __cuda_builtin_blockDim_t
#define uint3 __cuda_builtin_threadIdx_t
#include "curand_mtgp32_kernel.h"
#pragma pop_macro("dim3")
#pragma pop_macro("uint3")
#pragma pop_macro("__USE_FAST_MATH__")
#pragma pop_macro("__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__")

// CUDA runtime uses this undocumented function to access kernel launch
// configuration. The declaration is in crt/device_functions.h but that file
// includes a lot of other stuff we don't want. Instead, we'll provide our own
// declaration for it here.
#if CUDA_VERSION >= 9020
extern "C" unsigned __cudaPushCallConfiguration(dim3 gridDim, dim3 blockDim,
                                                size_t sharedMem = 0,
                                                void *stream = 0);
#endif

#endif // __CUDA__
#endif // __CLANG_CUDA_RUNTIME_WRAPPER_H__

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