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#include <torch/csrc/distributed/c10d/CUDASymmetricMemory.hpp>
#include <torch/csrc/distributed/c10d/CUDASymmetricMemory-inl.h>
#include <ATen/ceil_div.h>
#include <ATen/cuda/CUDAContext.h>
#include <c10/cuda/CUDACachingAllocator.h>
#include <c10/cuda/CUDAGuard.h>
#include <c10/util/error.h>
#if !defined(USE_ROCM) && defined(PYTORCH_C10_DRIVER_API_SUPPORTED)
#include <c10/cuda/driver_api.h>
#endif
#include <sys/socket.h>
#include <sys/syscall.h>
#include <sys/un.h>
#include <unistd.h>
#if defined(CUDART_VERSION) && CUDART_VERSION >= 12030
#define CUDART_SUPPORTS_MULTICAST
#endif
namespace {
bool device_has_multicast_support(int device_idx) {
#if defined(CUDART_SUPPORTS_MULTICAST)
if (c10::utils::check_env("TORCH_SYMM_MEM_DISABLE_MULTICAST") == true) {
return false;
}
// Multicast support requirements:
// - CUDA Runtime version >= 12030: Checked at compile time using
// CUDART_VERSION.
// - Driver version >= 535: Checked at runtime by verifying the existence of
// cuMulticastCreate_.
// - Device support: Determined by querying
// CU_DEVICE_ATTRIBUTE_MULTICAST_SUPPORTED at runtime.
auto driver_api = c10::cuda::DriverAPI::get();
int multicast_supported;
C10_CUDA_DRIVER_CHECK(driver_api->cuDeviceGetAttribute_(
&multicast_supported,
CU_DEVICE_ATTRIBUTE_MULTICAST_SUPPORTED,
device_idx));
return driver_api->cuMulticastCreate_ != nullptr && multicast_supported;
#else
return false;
#endif
}
bool allow_overlapping_devices() {
return c10::utils::check_env("TORCH_SYMM_MEM_ALLOW_OVERLAPPING_DEVICES") ==
true;
}
class IpcChannel {
public:
IpcChannel() : socket_name_(get_socket_name(getpid())) {
TORCH_CHECK(
(socket_ = socket(AF_UNIX, SOCK_DGRAM, 0)) != 0,
"Failed to create socket: ",
c10::utils::str_error(errno));
struct sockaddr_un addr = {.sun_family = AF_UNIX};
std::copy(socket_name_.begin(), socket_name_.end(), addr.sun_path);
TORCH_CHECK(
bind(socket_, (struct sockaddr*)&addr, SUN_LEN(&addr)) == 0,
"Failed to bind socket: ",
c10::utils::str_error(errno));
}
~IpcChannel() {
close(socket_);
unlink(socket_name_.c_str());
}
void send_fd(int dst_pid, int fd) {
struct sockaddr_un addr = {.sun_family = AF_UNIX};
auto socket_name = get_socket_name(dst_pid);
std::copy(socket_name.begin(), socket_name.end(), addr.sun_path);
struct iovec io = {.iov_base = (void*)("fd"), .iov_len = 2};
char cbuf[CMSG_SPACE(sizeof(int))];
memset(cbuf, 0, sizeof(cbuf));
struct msghdr msg {
.msg_name = (void*)&addr, .msg_namelen = sizeof(struct sockaddr_un),
.msg_iov = &io, .msg_iovlen = 1, .msg_control = cbuf,
.msg_controllen = sizeof(cbuf)
};
auto cmsg = CMSG_FIRSTHDR(&msg);
cmsg->cmsg_len = CMSG_LEN(sizeof(int));
cmsg->cmsg_level = SOL_SOCKET;
cmsg->cmsg_type = SCM_RIGHTS;
if (fd != -1) {
std::copy(
reinterpret_cast<const char*>(&fd),
reinterpret_cast<const char*>(&fd) + sizeof(fd),
reinterpret_cast<char*>(CMSG_DATA(cmsg)));
} else {
msg.msg_controllen = 0;
}
TORCH_CHECK(
sendmsg(socket_, &msg, 0) > 0, "Failed to send fd: ", c10::utils::str_error(errno));
}
int recv_fd() {
char buf[2];
struct iovec io = {.iov_base = (void*)buf, .iov_len = sizeof(buf)};
char cbuf[CMSG_SPACE(sizeof(int))];
memset(cbuf, 0, sizeof(cbuf));
struct msghdr msg = {
.msg_iov = &io,
.msg_iovlen = 1,
.msg_control = cbuf,
.msg_controllen = sizeof(cbuf)};
TORCH_CHECK(
recvmsg(socket_, &msg, 0) > 0,
"Failed to receive fd: ",
c10::utils::str_error(errno));
if (msg.msg_controllen == 0) {
return -1;
}
auto cmsg = CMSG_FIRSTHDR(&msg);
TORCH_CHECK(cmsg != NULL);
TORCH_CHECK(cmsg->cmsg_len == CMSG_LEN(sizeof(int)));
TORCH_CHECK(
cmsg->cmsg_level == SOL_SOCKET && cmsg->cmsg_type == SCM_RIGHTS);
return *reinterpret_cast<int*>(CMSG_DATA(cmsg));
}
std::vector<int> all_gather_fds(
int rank,
const std::vector<int>& pids,
int fd) {
size_t world_size = pids.size();
std::vector<int> fds(pids.size());
fds[rank] = fd;
int dst_rank = (rank + 1) % world_size;
for (size_t step = 1; step < world_size; ++step) {
int src_rank = (rank + world_size - step) % world_size;
send_fd(pids[dst_rank], fd);
fd = recv_fd();
fds[src_rank] = fd;
}
return fds;
}
int broadcast_fds(
int rank,
int src_rank,
const std::vector<int>& pids,
int fd) {
size_t world_size = pids.size();
if (rank == src_rank) {
for (int dst_rank = 0; dst_rank < (int)world_size; ++dst_rank) {
if (dst_rank == rank) {
continue;
}
send_fd(pids[dst_rank], fd);
}
return fd;
}
return recv_fd();
}
private:
static std::string get_socket_name(int pid) {
const char* tmp_dir = "/tmp";
for (const char* env_var : {"TMPDIR", "TMP", "TEMP", "TEMPDIR"}) {
if (const char* path = getenv(env_var)) {
tmp_dir = path;
break;
}
}
std::ostringstream oss;
oss << tmp_dir << "/symm_mem-" << pid;
return oss.str();
}
std::string socket_name_;
int socket_;
};
constexpr size_t signal_pad_size = 2048;
const std::string store_comm_prefix = "CUDASymmetricMemory";
static size_t store_comm_seq_id = 0;
template <typename T>
std::vector<T> store_all_gather(
const c10::intrusive_ptr<c10d::Store>& store,
int rank,
int world_size,
T val) {
static_assert(std::is_trivially_copyable_v<T>);
std::vector<std::string> peer_keys;
for (int r = 0; r < world_size; ++r) {
std::ostringstream oss;
oss << store_comm_prefix << "/" << store_comm_seq_id << "/" << r;
peer_keys.push_back(oss.str());
}
++store_comm_seq_id;
{
std::vector<uint8_t> payload(
reinterpret_cast<uint8_t*>(&val),
reinterpret_cast<uint8_t*>(&val) + sizeof(T));
store->set(peer_keys[rank], payload);
}
std::vector<T> peer_vals;
for (int r = 0; r < world_size; ++r) {
if (r == rank) {
peer_vals.push_back(val);
continue;
}
store->wait({peer_keys[r]});
auto payload = store->get(peer_keys[r]);
TORCH_CHECK(payload.size() == sizeof(T));
T peer_val{};
std::memcpy(&peer_val, payload.data(), sizeof(T));
peer_vals.push_back(peer_val);
}
return peer_vals;
}
void store_barrier(
const c10::intrusive_ptr<c10d::Store>& store,
int rank,
int world_size) {
store_all_gather(store, rank, world_size, 0);
}
void map_block(
void** ptr,
c10d::symmetric_memory::HandleType handle,
size_t size,
int device_idx) {
#if !defined(USE_ROCM) && defined(PYTORCH_C10_DRIVER_API_SUPPORTED)
auto driver_api = c10::cuda::DriverAPI::get();
auto dev_ptr = reinterpret_cast<CUdeviceptr*>(ptr);
C10_CUDA_DRIVER_CHECK(
driver_api->cuMemAddressReserve_(dev_ptr, size, 0ULL, 0, 0ULL));
C10_CUDA_DRIVER_CHECK(driver_api->cuMemMap_(*dev_ptr, size, 0, handle, 0ULL));
CUmemAccessDesc desc;
desc.location.type = CU_MEM_LOCATION_TYPE_DEVICE;
// NOLINTNEXTLINE(bugprone-signed-char-misuse)
desc.location.id = static_cast<int>(device_idx);
desc.flags = CU_MEM_ACCESS_FLAGS_PROT_READWRITE;
C10_CUDA_DRIVER_CHECK(driver_api->cuMemSetAccess_(*dev_ptr, size, &desc, 1));
#else
TORCH_CHECK(
false, "CUDASymmetricMemory requires PYTORCH_C10_DRIVER_API_SUPPORTED");
#endif
}
} // namespace
namespace c10d {
namespace symmetric_memory {
AllocationRef::AllocationRef(void* ptr, HandleType handle, size_t block_size, int device_idx)
: ptr(ptr), handle(handle), block_size(block_size), device_idx(device_idx) {}
AllocationRef::~AllocationRef() {
#if !defined(USE_ROCM) && defined(PYTORCH_C10_DRIVER_API_SUPPORTED)
// Leak the cuda allocations during static deinitialization
if (is_finalizing()) {
return;
}
auto driver_api = c10::cuda::DriverAPI::get();
c10::cuda::CUDAGuard guard(device_idx);
C10_CUDA_CHECK(cudaDeviceSynchronize());
C10_CUDA_DRIVER_CHECK(
driver_api->cuMemUnmap_(reinterpret_cast<CUdeviceptr>(ptr), block_size));
C10_CUDA_DRIVER_CHECK(driver_api->cuMemRelease_(handle));
#else
TORCH_CHECK(
false, "CUDASymmetricMemory requires PYTORCH_C10_DRIVER_API_SUPPORTED");
#endif
}
CUDASymmetricMemory::CUDASymmetricMemory(
std::vector<c10::intrusive_ptr<AllocationRef>> alloc_refs,
std::vector<void*> buffers,
std::vector<void*> signal_pads,
HandleType mc_handle,
void* mc_addr,
size_t buffer_size,
int local_device_idx,
int rank,
int world_size)
: alloc_refs_(std::move(alloc_refs)),
buffers_(std::move(buffers)),
signal_pads_(std::move(signal_pads)),
mc_handle_(mc_handle),
mc_addr_(mc_addr),
buffer_size_(buffer_size),
local_device_idx_(local_device_idx),
rank_(rank),
world_size_(world_size) {
const size_t arr_size = sizeof(void*) * world_size_;
buffers_dev_ = reinterpret_cast<void**>(
c10::cuda::CUDACachingAllocator::raw_alloc(arr_size));
signal_pads_dev_ = reinterpret_cast<void**>(
c10::cuda::CUDACachingAllocator::raw_alloc(arr_size));
c10::cuda::CUDAGuard guard(local_device_idx);
AT_CUDA_CHECK(cudaMemcpy(
buffers_dev_, buffers_.data(), arr_size, cudaMemcpyHostToDevice));
AT_CUDA_CHECK(cudaMemcpy(
signal_pads_dev_, signal_pads_.data(), arr_size, cudaMemcpyHostToDevice));
}
std::vector<void*> CUDASymmetricMemory::get_buffer_ptrs() {
return buffers_;
}
std::vector<void*> CUDASymmetricMemory::get_signal_pad_ptrs() {
return signal_pads_;
}
void** CUDASymmetricMemory::get_buffer_ptrs_dev() {
return buffers_dev_;
}
void** CUDASymmetricMemory::get_signal_pad_ptrs_dev() {
return signal_pads_dev_;
}
size_t CUDASymmetricMemory::get_buffer_size() {
return buffer_size_;
}
size_t CUDASymmetricMemory::get_signal_pad_size() {
return signal_pad_size;
}
bool CUDASymmetricMemory::has_multicast_support() {
return mc_addr_ != nullptr;
}
void* CUDASymmetricMemory::get_multicast_ptr() {
return mc_addr_;
}
at::Tensor CUDASymmetricMemory::get_buffer(
int rank,
c10::IntArrayRef sizes,
c10::ScalarType dtype,
int64_t storage_offset) {
const size_t numel = std::accumulate(
sizes.begin(),
sizes.end(),
static_cast<size_t>(1),
std::multiplies<size_t>());
const auto element_size = c10::elementSize(dtype);
const auto req_size = (numel + storage_offset) * element_size;
TORCH_CHECK(
req_size <= buffer_size_,
"CUDASymmetricMemory::get_buffer: the requested size (",
req_size,
" bytes) exceeds the allocated size (",
buffer_size_,
" bytes)");
auto data_ptr = reinterpret_cast<uint8_t*>(buffers_[rank]) +
storage_offset * element_size;
auto device = c10::Device(c10::DeviceType::CUDA, local_device_idx_);
auto options = at::TensorOptions().dtype(dtype).device(device);
return at::for_blob(data_ptr, sizes)
.options(options)
.target_device(device)
.make_tensor();
}
at::Tensor CUDASymmetricMemory::get_signal_pad(
int rank,
c10::IntArrayRef sizes,
std::optional<c10::ScalarType> dtype,
int64_t storage_offset) {
// If the dtype is unspecified, default it to UInt32, as it
// is the most common type for signaling purposes.
if (!dtype.has_value()) {
dtype = c10::ScalarType::UInt32;
}
// If the shape is unspecified, treat the signal pad as a 1d tensor.
const auto element_size = c10::elementSize(*dtype);
std::vector<int64_t> shape;
if (sizes.size() != 0) {
shape = sizes.vec();
} else {
shape.push_back(signal_pad_size / element_size);
}
const size_t numel = std::accumulate(
shape.begin(),
shape.end(),
static_cast<size_t>(1),
std::multiplies<size_t>());
const auto req_size = (numel + storage_offset) * element_size;
TORCH_CHECK(
req_size <= signal_pad_size,
"CUDASymmetricMemory::get_signal_pad: the requested size (",
req_size,
" bytes) exceeds the allocated size (",
signal_pad_size,
" bytes)");
auto data_ptr = reinterpret_cast<uint8_t*>(signal_pads_[rank]) +
storage_offset * element_size;
auto device = c10::Device(c10::DeviceType::CUDA, local_device_idx_);
auto options = at::TensorOptions().dtype(*dtype).device(device);
return at::for_blob(data_ptr, shape)
.options(options)
.target_device(device)
.make_tensor();
}
void check_channel(int channel, int world_size) {
TORCH_CHECK(
channel >= 0,
"channel for barrier(), put_signal() and wait_signal() ",
"must be greater than 0 (got ",
channel,
")");
const size_t num_channels = signal_pad_size / sizeof(uint32_t) * world_size;
TORCH_CHECK(
static_cast<size_t>(channel) < num_channels,
"The maximum supported channel for barrier(), put_signal() and wait_signal() is ",
num_channels - 1,
" (got ",
channel,
")");
}
static __global__ void barrier_kernel(
uint32_t** signal_pads,
int channel,
int rank,
int world_size,
size_t timeout_ms) {
if (threadIdx.x < world_size) {
auto target_rank = threadIdx.x;
if (target_rank == rank) {
return;
}
auto put_success = try_put_signal<MemOpSem::Release>(
signal_pads[target_rank] + world_size * channel + rank, timeout_ms);
if (!put_success) {
printf(
"[FATAL] CUDASymmetricMemory::barrier: rank %d failed to send signal "
"to rank %d on channel %d after %lu microseconds\n",
rank,
target_rank,
channel,
timeout_ms);
trap();
}
auto wait_success = try_wait_signal<MemOpSem::Acquire>(
signal_pads[rank] + world_size * channel + target_rank, timeout_ms);
if (!wait_success) {
printf(
"[FATAL] CUDASymmetricMemory::barrier: rank %d failed to receive signal "
"from rank %d on channel %d after %lu microseconds\n",
rank,
target_rank,
channel,
timeout_ms);
trap();
}
}
}
void CUDASymmetricMemory::barrier(int channel, size_t timeout_ms) {
check_channel(channel, world_size_);
c10::cuda::CUDAGuard guard(local_device_idx_);
barrier_kernel<<<1, C10_WARP_SIZE, 0, at::cuda::getCurrentCUDAStream()>>>(
reinterpret_cast<uint32_t**>(signal_pads_dev_),
channel,
rank_,
world_size_,
timeout_ms);
C10_CUDA_KERNEL_LAUNCH_CHECK();
}
static __global__ void put_signal_kernel(
uint32_t** signal_pads,
int dst_rank,
int channel,
int rank,
int world_size,
size_t timeout_ms) {
if (threadIdx.x == 0) {
bool success = try_put_signal<MemOpSem::Release>(
signal_pads[dst_rank] + world_size * channel + rank, timeout_ms);
if (!success) {
printf(
"[FATAL] CUDASymmetricMemory::put_signal: rank %d failed to send signal "
"to rank %d on channel %d after %lu microseconds\n",
rank,
dst_rank,
channel,
timeout_ms);
trap();
}
}
}
void CUDASymmetricMemory::put_signal(
int dst_rank,
int channel,
size_t timeout_ms) {
check_channel(channel, world_size_);
c10::cuda::CUDAGuard guard(local_device_idx_);
put_signal_kernel<<<1, C10_WARP_SIZE, 0, at::cuda::getCurrentCUDAStream()>>>(
reinterpret_cast<uint32_t**>(signal_pads_dev_),
dst_rank,
channel,
rank_,
world_size_,
timeout_ms);
C10_CUDA_KERNEL_LAUNCH_CHECK();
}
static __global__ void wait_signal_kernel(
uint32_t** signal_pads,
int src_rank,
int channel,
int rank,
int world_size,
size_t timeout_ms) {
if (threadIdx.x == 0) {
bool success = try_wait_signal<MemOpSem::Acquire>(
signal_pads[rank] + world_size * channel + src_rank, timeout_ms);
if (!success) {
printf(
"[FATAL] CUDASymmetricMemory::wait_signal rank %d failed to receive signal "
"from rank %d on channel %d after %lu microseconds\n",
rank,
src_rank,
channel,
timeout_ms);
#if !defined(USE_ROCM)
__trap();
#else
assert(0);
#endif
}
}
__threadfence_system();
}
void CUDASymmetricMemory::wait_signal(
int src_rank,
int channel,
size_t timeout_ms) {
check_channel(channel, world_size_);
c10::cuda::CUDAGuard guard(local_device_idx_);
wait_signal_kernel<<<1, C10_WARP_SIZE, 0, at::cuda::getCurrentCUDAStream()>>>(
reinterpret_cast<uint32_t**>(signal_pads_dev_),
src_rank,
channel,
rank_,
world_size_,
timeout_ms);
C10_CUDA_KERNEL_LAUNCH_CHECK();
}
int CUDASymmetricMemory::get_rank() {
return rank_;
}
int CUDASymmetricMemory::get_world_size() {
return world_size_;
}
Block::Block(
c10::intrusive_ptr<AllocationRef> alloc_ref,
int device_idx,
size_t block_size,
size_t buffer_size,
size_t signal_pad_offset,
const std::optional<std::string>& group_name)
: alloc_ref(std::move(alloc_ref)),
device_idx(device_idx),
block_size(block_size),
buffer_size(buffer_size),
signal_pad_offset(signal_pad_offset),
default_group_name(std::move(group_name)) {}
void* CUDASymmetricMemoryAllocator::alloc(
size_t size,
int device_idx,
const std::optional<std::string>& group_name) {
#if !defined(USE_ROCM) && defined(PYTORCH_C10_DRIVER_API_SUPPORTED)
c10::cuda::CUDAGuard guard(device_idx);
device_idx = static_cast<int>(guard.current_device().index());
CUmemAllocationProp prop = {};
prop.type = CU_MEM_ALLOCATION_TYPE_PINNED;
prop.location.type = CU_MEM_LOCATION_TYPE_DEVICE;
// NOLINTNEXTLINE(bugprone-signed-char-misuse)
prop.location.id = device_idx;
prop.requestedHandleTypes = CU_MEM_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR;
size_t signal_pad_offset = at::round_up(size, 16UL);
size_t block_size = signal_pad_offset + signal_pad_size;
size_t granularity;
auto driver_api = c10::cuda::DriverAPI::get();
C10_CUDA_DRIVER_CHECK(driver_api->cuMemGetAllocationGranularity_(
&granularity, &prop, CU_MEM_ALLOC_GRANULARITY_RECOMMENDED));
block_size = at::round_up(block_size, granularity);
HandleType handle;
C10_CUDA_DRIVER_CHECK(
driver_api->cuMemCreate_(&handle, block_size, &prop, 0));
void* ptr = nullptr;
map_block(&ptr, handle, block_size, device_idx);
AT_CUDA_CHECK(cudaMemset(ptr, 0, block_size));
auto alloc_ref = c10::make_intrusive<AllocationRef>(ptr, handle, block_size, device_idx);
auto block = c10::make_intrusive<Block>(
std::move(alloc_ref),
device_idx,
block_size,
size,
signal_pad_offset,
group_name);
{
std::unique_lock lock(mutex_);
ptr_to_block_.emplace(ptr, std::move(block));
}
return ptr;
#else
TORCH_CHECK(
false, "CUDASymmetricMemory requires PYTORCH_C10_DRIVER_API_SUPPORTED");
#endif
}
void CUDASymmetricMemoryAllocator::free(void* ptr) {
std::unique_lock lock(mutex_);
ptr_to_block_.erase(ptr);
}
size_t CUDASymmetricMemoryAllocator::get_alloc_size(void* ptr) {
auto block = find_block(ptr);
TORCH_CHECK(
block != nullptr,
"CUDASymmetricMemoryAllocator::get_alloc_size: input must be allocated ",
"via CUDASymmetricMemoryAllocator::alloc");
return block->buffer_size;
}
struct RendezvousRequest {
int device_idx;
int pid;
size_t block_size;
size_t buffer_size;
size_t signal_pad_offset;
bool has_multicast_support;
};
void validate_rendezvous_requests(
const std::vector<RendezvousRequest>& reqs,
int world_size) {
TORCH_CHECK(reqs.size() == (size_t)world_size);
std::unordered_set<int> device_indices;
device_indices.reserve(world_size);
for (auto req : reqs) {
device_indices.insert(req.device_idx);
}
if (!allow_overlapping_devices() &&
device_indices.size() < (size_t)world_size) {
TORCH_CHECK(
false,
"CUDASymmetricMemoryAllocator::rendezvous: ",
"detected allocations from overlapping devices ",
"from different ranks.");
}
for (int r = 1; r < world_size; ++r) {
TORCH_CHECK(reqs[r].block_size == reqs[0].block_size);
TORCH_CHECK(reqs[r].buffer_size == reqs[0].buffer_size);
TORCH_CHECK(reqs[r].signal_pad_offset == reqs[0].signal_pad_offset);
}
}
static bool check_group_multicast_support(
const std::vector<RendezvousRequest>& reqs) {
std::vector<size_t> ranks_with_multicast_support;
for (size_t r = 0; r < reqs.size(); ++r) {
if (reqs[r].has_multicast_support) {
ranks_with_multicast_support.push_back(r);
}
}
if (ranks_with_multicast_support.size() == reqs.size()) {
return true;
} else {
// We don't expect this to happen. But we want to let the user to know if
// this happens.
if (ranks_with_multicast_support.size() != 0) {
LOG(WARNING)
<< "Only a subset of ranks in the group has multicast support: "
<< ranks_with_multicast_support << " (world_size=" << reqs.size()
<< "). Skipping multicast initialization because this is unexpected.";
}
return false;
}
}
static void init_multicast_for_block(
HandleType& mc_handle,
void*& mc_addr,
const c10::intrusive_ptr<Block>& block,
IpcChannel& ipc_channel,
const std::vector<int>& pids,
const c10::intrusive_ptr<c10d::Store>& store,
int rank,
int world_size) {
#if !defined(USE_ROCM) && defined(PYTORCH_C10_DRIVER_API_SUPPORTED) && \
defined(CUDART_SUPPORTS_MULTICAST)
auto driver_api = c10::cuda::DriverAPI::get();
if (rank == 0) {
CUmulticastObjectProp mc_prop{};
mc_prop.numDevices = world_size;
mc_prop.handleTypes = CU_MEM_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR;
mc_prop.size = block->block_size;
auto err = driver_api->cuMulticastCreate_(&mc_handle, &mc_prop);
if (err != CUDA_SUCCESS) {
const char* err_str;
CUresult get_error_str_err = driver_api->cuGetErrorString_(err, &err_str);
if (get_error_str_err != CUDA_SUCCESS) {
err_str = "unknown cuda driver error";
}
LOG(WARNING)
<< "SymmetricMemory: cuMulticastCreate failed with: \"" << err_str
<< "\". Gracefully skipping multicast initialization. "
<< "However, this is unexpected. Please report the issue on GitHub.";
// Allow peers gracefully skip multicast initialization by sending -1
ipc_channel.broadcast_fds(rank, 0, pids, -1);
return;
}
int mc_fd;
C10_CUDA_DRIVER_CHECK(driver_api->cuMemExportToShareableHandle_(
&mc_fd, mc_handle, CU_MEM_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR, 0));
ipc_channel.broadcast_fds(rank, 0, pids, mc_fd);
// Ref count is incremented as soon as SCM_RIGHTS send happens
close(mc_fd);
} else {
int mc_fd = ipc_channel.broadcast_fds(rank, 0, pids, -1);
if (mc_fd == -1) {
return;
}
C10_CUDA_DRIVER_CHECK(driver_api->cuMemImportFromShareableHandle_(
&mc_handle,
(void*)(uintptr_t)mc_fd,
CU_MEM_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR));
close(mc_fd);
}
// All rank adds their physical allocation to the multicast object
C10_CUDA_DRIVER_CHECK(
driver_api->cuMulticastAddDevice_(mc_handle, block->device_idx));
C10_CUDA_DRIVER_CHECK(driver_api->cuMulticastBindMem_(
mc_handle, 0, block->alloc_ref->handle, 0, block->block_size, 0));
map_block(&mc_addr, mc_handle, block->block_size, block->device_idx);
store_barrier(store, rank, world_size);
#endif
}
c10::intrusive_ptr<SymmetricMemory> CUDASymmetricMemoryAllocator::rendezvous(
void* ptr,
const std::optional<std::string>& group_name) {
#if !defined(USE_ROCM) && defined(PYTORCH_C10_DRIVER_API_SUPPORTED)
auto block = find_block(ptr);
if (block == nullptr) {
return nullptr;
}
// The group_name passed to rendezvous() takes precedence over
// the default group_name specified during allocation.
std::string group_name_;
if (group_name.has_value()) {
group_name_ = *group_name;
} else {
if (!block->default_group_name.has_value()) {
TORCH_CHECK(
false,
"CUDASymmetricMemory::rendezvous: `group_name` is neither "
"specified during allocation nor passed to rendezvous().");
}
group_name_ = *block->default_group_name;
}
auto it = block->symm_mems.find(group_name_);
if (it != block->symm_mems.end()) {
return it->second;
}
IpcChannel ipc_channel;
auto group_info = get_group_info(group_name_);
auto store = group_info.store;
int rank = group_info.rank;
int world_size = group_info.world_size;
auto driver_api = c10::cuda::DriverAPI::get();
int block_fd;
C10_CUDA_DRIVER_CHECK(driver_api->cuMemExportToShareableHandle_(
&block_fd,
block->alloc_ref->handle,
CU_MEM_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR,
0));
auto local_req = RendezvousRequest{
.device_idx = block->device_idx,
.pid = getpid(),
.block_size = block->block_size,
.buffer_size = block->buffer_size,
.signal_pad_offset = block->signal_pad_offset,
.has_multicast_support = device_has_multicast_support(block->device_idx)};
auto reqs = store_all_gather(store, rank, world_size, local_req);
validate_rendezvous_requests(reqs, world_size);
std::vector<int> pids(world_size);
for (int r = 0; r < world_size; ++r) {
pids[r] = reqs[r].pid;
}
auto imported_fds = ipc_channel.all_gather_fds(rank, pids, block_fd);
std::vector<HandleType> handles(world_size);
std::vector<void*> buffers(world_size, nullptr);
std::vector<void*> signal_pads(world_size, nullptr);
for (int r = 0; r < world_size; ++r) {
if (r == rank) {
handles[r] = block->alloc_ref->handle;
buffers[r] = ptr;
signal_pads[r] = (void*)((uintptr_t)ptr + block->signal_pad_offset);
continue;
}
C10_CUDA_DRIVER_CHECK(driver_api->cuMemImportFromShareableHandle_(
&handles[r],
(void*)(uintptr_t)imported_fds[r],
CU_MEM_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR));
map_block(&buffers[r], handles[r], block->block_size, block->device_idx);
signal_pads[r] = (void*)((uintptr_t)buffers[r] + block->signal_pad_offset);
close(imported_fds[r]);
}
store_barrier(store, rank, world_size);
close(block_fd);
HandleType mc_handle{};
void* mc_addr = nullptr;
bool group_has_multicast_support = check_group_multicast_support(reqs);
if (!allow_overlapping_devices() && group_has_multicast_support) {
init_multicast_for_block(
mc_handle, mc_addr, block, ipc_channel, pids, store, rank, world_size);
}
std::vector<c10::intrusive_ptr<AllocationRef>> alloc_refs;
for (int r = 0; r < world_size; ++r) {
if (r == rank) {
alloc_refs.emplace_back(block->alloc_ref);
continue;
}
alloc_refs.push_back(c10::make_intrusive<AllocationRef>(
buffers[r], handles[r], block->block_size, block->device_idx));
}
auto symm_mem = c10::make_intrusive<CUDASymmetricMemory>(
std::move(alloc_refs),
std::move(buffers),
std::move(signal_pads),
mc_handle,
mc_addr,
block->buffer_size,
block->device_idx,
group_info.rank,
group_info.world_size);
block->symm_mems[group_name_] = symm_mem;
return symm_mem;
#else
TORCH_CHECK(
false, "CUDASymmetricMemory requires PYTORCH_C10_DRIVER_API_SUPPORTED");
#endif
}
bool CUDASymmetricMemoryAllocator::has_multicast_support(int device_idx) {
return device_has_multicast_support(device_idx);
}
c10::intrusive_ptr<Block> CUDASymmetricMemoryAllocator::find_block(void* ptr) {
std::shared_lock lock(mutex_);
auto it = ptr_to_block_.find(ptr);
if (it == ptr_to_block_.end()) {
return nullptr;
}
return it->second;
}
struct RegisterCUDASymmetricMemoryAllocator {
RegisterCUDASymmetricMemoryAllocator() {
register_allocator(
c10::DeviceType::CUDA,
c10::make_intrusive<CUDASymmetricMemoryAllocator>());
}
};
static RegisterCUDASymmetricMemoryAllocator register_allocator_;
} // namespace symmetric_memory
} // namespace c10d
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