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151 changes: 123 additions & 28 deletions src/llama-mmap.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -13,9 +13,10 @@
#ifdef __has_include
#if __has_include(<unistd.h>)
#include <unistd.h>
#include <fcntl.h>
#include <sys/stat.h>
#if defined(_POSIX_MAPPED_FILES)
#include <sys/mman.h>
#include <fcntl.h>
#endif
#if defined(_POSIX_MEMLOCK_RANGE)
#include <sys/resource.h>
Expand Down Expand Up @@ -74,7 +75,7 @@ struct llama_file::impl {
return ret;
}

impl(const char * fname, const char * mode) {
impl(const char * fname, const char * mode, [[maybe_unused]] const bool use_direct_io = false) {
fp = ggml_fopen(fname, mode);
if (fp == NULL) {
throw std::runtime_error(format("failed to open %s: %s", fname, strerror(errno)));
Expand Down Expand Up @@ -153,13 +154,40 @@ struct llama_file::impl {
write_raw(&val, sizeof(val));
}

void read_aligned_chunk(size_t offset, void * dest, size_t size) const {
throw std::runtime_error("DirectIO is not implemented on Windows.");
}

~impl() {
if (fp) {
std::fclose(fp);
}
}
#else
impl(const char * fname, const char * mode) {
impl(const char * fname, const char * mode, [[maybe_unused]] const bool use_direct_io = false) {
#ifdef __linux__
// Try unbuffered I/O for read only
if (use_direct_io && std::strcmp(mode, "rb") == 0) {
fd = open(fname, O_RDONLY | O_DIRECT);

if (fd != -1) {
struct stat file_stats{};
fstat(fd, &file_stats);

size = file_stats.st_size;
alignment = file_stats.st_blksize;

off_t ret = lseek(fd, 0, SEEK_SET);
if (ret == -1) {
throw std::runtime_error(format("seek error: %s", strerror(errno)));
}
return;
}

LLAMA_LOG_WARN("Failed to open model %s with error: %s. Falling back to buffered I/O",
fname, strerror(errno));
}
#endif
fp = ggml_fopen(fname, mode);
if (fp == NULL) {
throw std::runtime_error(format("failed to open %s: %s", fname, strerror(errno)));
Expand All @@ -170,27 +198,30 @@ struct llama_file::impl {
}

size_t tell() const {
// TODO: this ifdef is never true?
#ifdef _WIN32
__int64 ret = _ftelli64(fp);
#else
long ret = std::ftell(fp);
#endif
if (ret == -1) {
throw std::runtime_error(format("ftell error: %s", strerror(errno)));
if (fd == -1) {
long ret = std::ftell(fp);
if (ret == -1) {
throw std::runtime_error(format("ftell error: %s", strerror(errno)));
}

return (size_t) ret;
}

return (size_t) ret;
off_t pos = lseek(fd, 0, SEEK_CUR);
if (pos == -1) {
throw std::runtime_error(format("lseek error: %s", strerror(errno)));
}
return (size_t) pos;
}

void seek(size_t offset, int whence) const {
// TODO: this ifdef is never true?
#ifdef _WIN32
int ret = _fseeki64(fp, (__int64) offset, whence);
#else
int ret = std::fseek(fp, (long) offset, whence);
#endif
if (ret != 0) {
off_t ret = 0;
if (fd == -1) {
ret = std::fseek(fp, (long) offset, whence);
} else {
ret = lseek(fd, offset, whence);
}
if (ret == -1) {
throw std::runtime_error(format("seek error: %s", strerror(errno)));
}
}
Expand All @@ -200,13 +231,55 @@ struct llama_file::impl {
return;
}
errno = 0;
std::size_t ret = std::fread(ptr, len, 1, fp);
if (ferror(fp)) {
throw std::runtime_error(format("read error: %s", strerror(errno)));
if (fd == -1) {
std::size_t ret = std::fread(ptr, len, 1, fp);
if (ferror(fp)) {
throw std::runtime_error(format("read error: %s", strerror(errno)));
}
if (ret != 1) {
throw std::runtime_error("unexpectedly reached end of file");
}
} else {
bool successful = false;
while (!successful) {
off_t ret = read(fd, ptr, len);

if (ret == -1) {
if (errno == EINTR) {
continue; // Interrupted by signal, retry
}
throw std::runtime_error(format("read error: %s", strerror(errno)));
}
if (ret == 0) {
throw std::runtime_error("unexpectedly reached end of file");
}

successful = true;
}
}
if (ret != 1) {
throw std::runtime_error("unexpectedly reached end of file");
}

void read_aligned_chunk(size_t offset, void * dest, size_t size) const {
off_t aligned_offset = offset & ~(alignment - 1);
off_t offset_from_alignment = offset - aligned_offset;
size_t bytes_to_read = (offset_from_alignment + size + alignment - 1) & ~(alignment - 1);

void * raw_buffer = nullptr;
int ret = posix_memalign(&raw_buffer, alignment, bytes_to_read);
if (ret != 0) {
throw std::runtime_error(format("posix_memalign failed with error %d", ret));
}

struct aligned_buffer_deleter {
void operator()(void * p) const { free(p); }
};
std::unique_ptr<void, aligned_buffer_deleter> buffer(raw_buffer);

seek(aligned_offset, SEEK_SET);
read_raw(buffer.get(), bytes_to_read);

uintptr_t actual_data = reinterpret_cast<uintptr_t>(buffer.get()) + offset_from_alignment;
memcpy(dest, reinterpret_cast<void *>(actual_data), size);
}

uint32_t read_u32() const {
Expand All @@ -231,22 +304,43 @@ struct llama_file::impl {
}

~impl() {
if (fp) {
if (fd != -1) {
close(fd);
} else {
std::fclose(fp);
}
}
int fd = -1;
#endif

FILE * fp;
size_t size;
void read_raw_at(void * ptr, size_t len, size_t offset) const {
if (alignment != 1) {
read_aligned_chunk(offset, ptr, len);
} else {
seek(offset, SEEK_SET);
read_raw(ptr, len);
}
}

size_t read_alignment() const {
return alignment;
}

size_t alignment = 1;

FILE * fp{};
size_t size{};
};

llama_file::llama_file(const char * fname, const char * mode) : pimpl(std::make_unique<impl>(fname, mode)) {}
llama_file::llama_file(const char * fname, const char * mode, const bool use_direct_io) :
pimpl(std::make_unique<impl>(fname, mode, use_direct_io)) {}
llama_file::~llama_file() = default;

size_t llama_file::tell() const { return pimpl->tell(); }
size_t llama_file::size() const { return pimpl->size; }

size_t llama_file::read_alignment() const { return pimpl->read_alignment(); }

int llama_file::file_id() const {
#ifdef _WIN32
return _fileno(pimpl->fp);
Expand All @@ -261,6 +355,7 @@ int llama_file::file_id() const {

void llama_file::seek(size_t offset, int whence) const { pimpl->seek(offset, whence); }
void llama_file::read_raw(void * ptr, size_t len) const { pimpl->read_raw(ptr, len); }
void llama_file::read_raw_at(void * ptr, size_t len, size_t offset) const { pimpl->read_raw_at(ptr, len, offset); }

uint32_t llama_file::read_u32() const { return pimpl->read_u32(); }

Expand Down
6 changes: 5 additions & 1 deletion src/llama-mmap.h
Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@
#include <cstdint>
#include <memory>
#include <vector>
#include <cstdio>

struct llama_file;
struct llama_mmap;
Expand All @@ -13,7 +14,7 @@ using llama_mmaps = std::vector<std::unique_ptr<llama_mmap>>;
using llama_mlocks = std::vector<std::unique_ptr<llama_mlock>>;

struct llama_file {
llama_file(const char * fname, const char * mode);
llama_file(const char * fname, const char * mode, bool use_direct_io = false);
~llama_file();

size_t tell() const;
Expand All @@ -24,11 +25,14 @@ struct llama_file {
void seek(size_t offset, int whence) const;

void read_raw(void * ptr, size_t len) const;
void read_raw_at(void * ptr, size_t len, size_t offset) const;
void read_aligned_chunk(size_t offset, void * dest, size_t size) const;
uint32_t read_u32() const;

void write_raw(const void * ptr, size_t len) const;
void write_u32(uint32_t val) const;

size_t read_alignment() const;
private:
struct impl;
std::unique_ptr<impl> pimpl;
Expand Down
69 changes: 56 additions & 13 deletions src/llama-model-loader.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -503,7 +503,7 @@ llama_model_loader::llama_model_loader(
get_key(llm_kv(LLM_KV_GENERAL_ARCHITECTURE), arch_name, false);
llm_kv = LLM_KV(llm_arch_from_string(arch_name));

files.emplace_back(new llama_file(fname.c_str(), "rb"));
files.emplace_back(new llama_file(fname.c_str(), "rb", !use_mmap));
contexts.emplace_back(ctx);

// Save tensors data offset of the main file.
Expand Down Expand Up @@ -571,7 +571,7 @@ llama_model_loader::llama_model_loader(
}
}

files.emplace_back(new llama_file(fname_split, "rb"));
files.emplace_back(new llama_file(fname_split, "rb", !use_mmap));
contexts.emplace_back(ctx);

// Save tensors data offset info of the shard.
Expand Down Expand Up @@ -933,7 +933,15 @@ bool llama_model_loader::load_all_data(
// 4 staging buffers for async uploads, each sized 1MB seems to be a good default for single NVMe drives.
// NVMe raid configurations might require more / larger buffers.
constexpr size_t n_buffers = 4;
constexpr size_t buffer_size = 1 * 1024 * 1024; // 1MB

size_t alignment = 1;
for (const auto & file : files) {
alignment = std::max(file->read_alignment(), alignment);
}

// Buffer size: balance between memory usage and I/O efficiency
// 64MB works well for NVMe drives
const size_t buffer_size = alignment != 1 ? 64 * 1024 * 1024 + 2 * alignment : 1 * 1024 * 1024;

std::vector<ggml_backend_buffer_t> host_buffers;
std::vector<ggml_backend_event_t> events;
Expand Down Expand Up @@ -983,6 +991,7 @@ bool llama_model_loader::load_all_data(
// If the backend is supported, create pinned memory buffers and events for synchronisation.
for (size_t idx = 0; idx < n_buffers; ++idx) {
auto * buf = ggml_backend_buft_alloc_buffer(host_buft, buffer_size);

if (!buf) {
LLAMA_LOG_DEBUG("%s: failed to allocate host buffer for async uploads for device %s\n", func,
ggml_backend_dev_name(dev));
Expand Down Expand Up @@ -1064,9 +1073,9 @@ bool llama_model_loader::load_all_data(
}
} else {
const auto & file = files.at(weight->idx);

if (ggml_backend_buffer_is_host(cur->buffer)) {
file->seek(weight->offs, SEEK_SET);
file->read_raw(cur->data, n_size);
file->read_raw_at(cur->data, n_size, weight->offs);
if (check_tensors) {
validation_result.emplace_back(std::async(std::launch::async, [cur, n_size] {
return std::make_pair(cur, ggml_validate_row_data(cur->type, cur->data, n_size));
Expand All @@ -1075,26 +1084,60 @@ bool llama_model_loader::load_all_data(
} else {
// If upload_backend is valid load the tensor in chunks to pinned memory and upload the buffers asynchronously to the GPU.
if (upload_backend) {
file->seek(weight->offs, SEEK_SET);
auto offset = (off_t) weight->offs;
alignment = file->read_alignment();
off_t aligned_offset = offset & ~(alignment - 1);
off_t offset_from_alignment = offset - aligned_offset;
file->seek(aligned_offset, SEEK_SET);

// Calculate aligned read boundaries
size_t read_start = aligned_offset;
size_t read_end = (offset + n_size + alignment - 1) & ~(alignment - 1);

size_t bytes_read = 0;
size_t data_read = 0; // Actual tensor data copied (excluding padding)

while (bytes_read < read_end - read_start) {
size_t read_size = std::min<size_t>(buffer_size, read_end - read_start - bytes_read);

while (bytes_read < n_size) {
size_t read_iteration = std::min<size_t>(buffer_size, n_size - bytes_read);
// Align the destination pointer within the pinned buffer
uintptr_t ptr_dest_aligned = (reinterpret_cast<uintptr_t>(host_ptrs[buffer_idx]) + alignment - 1) & ~(alignment - 1);

// Wait for previous upload to complete before reusing buffer
ggml_backend_event_synchronize(events[buffer_idx]);
file->read_raw(host_ptrs[buffer_idx], read_iteration);
ggml_backend_tensor_set_async(upload_backend, cur, host_ptrs[buffer_idx], bytes_read, read_iteration);

// Read aligned chunk from file
file->read_raw(reinterpret_cast<void *>(ptr_dest_aligned), read_size);

// Calculate actual data portion (excluding alignment padding)
uintptr_t ptr_data = ptr_dest_aligned;
size_t data_to_copy = read_size;

// Skip alignment padding at start of first chunk
if (bytes_read == 0) {
ptr_data += offset_from_alignment;
data_to_copy -= offset_from_alignment;
}

// Trim alignment padding at end of last chunk
if (aligned_offset + bytes_read + read_size > offset + n_size) {
data_to_copy -= (read_end - (offset + n_size));
}

// Async upload actual data to GPU
ggml_backend_tensor_set_async(upload_backend, cur,
reinterpret_cast<void *>(ptr_data), data_read, data_to_copy);
ggml_backend_event_record(events[buffer_idx], upload_backend);

bytes_read += read_iteration;
data_read += data_to_copy;
bytes_read += read_size;

++buffer_idx;
buffer_idx %= n_buffers;
}
} else {
read_buf.resize(n_size);
file->seek(weight->offs, SEEK_SET);
file->read_raw(read_buf.data(), n_size);
file->read_raw_at(read_buf.data(), n_size, weight->offs);
ggml_backend_tensor_set(cur, read_buf.data(), 0, n_size);
if (check_tensors && !ggml_validate_row_data(cur->type, read_buf.data(), n_size)) {
throw std::runtime_error(format("tensor '%s' has invalid data", ggml_get_name(cur)));
Expand Down
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