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sync : ggml (ggml-backend) #3548

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merged 2 commits into from
Oct 8, 2023
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sync : ggml (ggml-backend) #3548

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20fad2e
sync : ggml (ggml-backend)
ggerganov Oct 8, 2023
2fafc15
zig : add ggml-backend to the build
ggerganov Oct 8, 2023
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2 changes: 2 additions & 0 deletions CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -663,6 +663,8 @@ add_library(ggml OBJECT
ggml.h
ggml-alloc.c
ggml-alloc.h
ggml-backend.c
ggml-backend.h
${GGML_SOURCES_CUDA} ${GGML_HEADERS_CUDA}
${GGML_SOURCES_OPENCL} ${GGML_HEADERS_OPENCL}
${GGML_SOURCES_METAL} ${GGML_HEADERS_METAL}
Expand Down
7 changes: 5 additions & 2 deletions Makefile
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Expand Up @@ -512,9 +512,12 @@ ggml.o: ggml.c ggml.h ggml-cuda.h
ggml-alloc.o: ggml-alloc.c ggml.h ggml-alloc.h
$(CC) $(CFLAGS) -c $< -o $@

OBJS += ggml-alloc.o
ggml-backend.o: ggml-backend.c ggml.h ggml-backend.h
$(CC) $(CFLAGS) -c $< -o $@

OBJS += ggml-alloc.o ggml-backend.o

llama.o: llama.cpp ggml.h ggml-alloc.h ggml-cuda.h ggml-metal.h llama.h
llama.o: llama.cpp ggml.h ggml-alloc.h ggml-backend.h ggml-cuda.h ggml-metal.h llama.h
$(CXX) $(CXXFLAGS) -c $< -o $@

common.o: common/common.cpp common/common.h build-info.h common/log.h
Expand Down
15 changes: 8 additions & 7 deletions build.zig
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Original file line number Diff line number Diff line change
Expand Up @@ -124,20 +124,21 @@ pub fn build(b: *std.build.Builder) !void {

const ggml = make.obj("ggml", "ggml.c");
const ggml_alloc = make.obj("ggml-alloc", "ggml-alloc.c");
const ggml_backend = make.obj("ggml-backend", "ggml-backend.c");
const llama = make.obj("llama", "llama.cpp");
const common = make.obj("common", "common/common.cpp");
const console = make.obj("console", "common/console.cpp");
const grammar_parser = make.obj("grammar-parser", "common/grammar-parser.cpp");
const train = make.obj("train", "common/train.cpp");

_ = make.exe("main", "examples/main/main.cpp", &.{ ggml, ggml_alloc, llama, common, console, grammar_parser });
_ = make.exe("quantize", "examples/quantize/quantize.cpp", &.{ ggml, ggml_alloc, llama, common });
_ = make.exe("perplexity", "examples/perplexity/perplexity.cpp", &.{ ggml, ggml_alloc, llama, common });
_ = make.exe("embedding", "examples/embedding/embedding.cpp", &.{ ggml, ggml_alloc, llama, common });
_ = make.exe("finetune", "examples/finetune/finetune.cpp", &.{ ggml, ggml_alloc, llama, common, train });
_ = make.exe("train-text-from-scratch", "examples/train-text-from-scratch/train-text-from-scratch.cpp", &.{ ggml, ggml_alloc, llama, common, train });
_ = make.exe("main", "examples/main/main.cpp", &.{ ggml, ggml_alloc, ggml_backend, llama, common, console, grammar_parser });
_ = make.exe("quantize", "examples/quantize/quantize.cpp", &.{ ggml, ggml_alloc, ggml_backend, llama, common });
_ = make.exe("perplexity", "examples/perplexity/perplexity.cpp", &.{ ggml, ggml_alloc, ggml_backend, llama, common });
_ = make.exe("embedding", "examples/embedding/embedding.cpp", &.{ ggml, ggml_alloc, ggml_backend, llama, common });
_ = make.exe("finetune", "examples/finetune/finetune.cpp", &.{ ggml, ggml_alloc, ggml_backend, llama, common, train });
_ = make.exe("train-text-from-scratch", "examples/train-text-from-scratch/train-text-from-scratch.cpp", &.{ ggml, ggml_alloc, ggml_backend, llama, common, train });

const server = make.exe("server", "examples/server/server.cpp", &.{ ggml, ggml_alloc, llama, common, grammar_parser });
const server = make.exe("server", "examples/server/server.cpp", &.{ ggml, ggml_alloc, ggml_backend, llama, common, grammar_parser });
if (server.target.isWindows()) {
server.linkSystemLibrary("ws2_32");
}
Expand Down
169 changes: 62 additions & 107 deletions ggml-alloc.c
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Original file line number Diff line number Diff line change
@@ -1,30 +1,12 @@
#include "ggml-alloc.h"
#include "ggml-backend.h"
#include "ggml.h"
#include <assert.h>
#include <stdarg.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>

#ifdef __has_include
#if __has_include(<unistd.h>)
#include <unistd.h>
#if defined(_POSIX_MAPPED_FILES)
#include <sys/types.h>
#include <sys/mman.h>
#endif
#endif
#endif

#if defined(_WIN32)
#define WIN32_LEAN_AND_MEAN
#ifndef NOMINMAX
#define NOMINMAX
#endif
#include <windows.h>
#include <memoryapi.h>
#endif


#define UNUSED(x) (void)(x)
#define MAX(a, b) ((a) > (b) ? (a) : (b))
Expand Down Expand Up @@ -80,8 +62,9 @@ struct free_block {
#define MAX_FREE_BLOCKS 256

struct ggml_allocr {
struct ggml_backend_buffer * buffer;
bool buffer_owned;
void * data;
size_t size;
size_t alignment;
int n_free_blocks;
struct free_block free_blocks[MAX_FREE_BLOCKS];
Expand Down Expand Up @@ -119,28 +102,20 @@ static void remove_allocated_tensor(struct ggml_allocr * alloc, struct ggml_tens
}
#endif

static size_t ggml_allocr_get_alloc_size(struct ggml_allocr * alloc, struct ggml_tensor * tensor) {
return ggml_nbytes(tensor);

UNUSED(alloc);
}

// check if a tensor is allocated by this buffer
static bool ggml_allocr_is_own(struct ggml_allocr * alloc, const struct ggml_tensor * tensor) {
void * ptr = tensor->data;
return ptr >= alloc->data && (char *)ptr < (char *)alloc->data + alloc->max_size;
return tensor->buffer == alloc->buffer;
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@xaedes xaedes Dec 21, 2023 •
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In train & finetune I make new allocator, allocate tensors, free the allocator and then repeat that for different groups of tensors.
Before this change the actual data pointer was used to check ownership. This pointer differed between successive allocators due to a different data buffer.
But the buffer member used here may not differ, because it is malloced by ggml_backend_buffer_init. It actually happens that the previous memory address is used, because the previous allocator along with its buffer was freed.

So with this change ggml_allocr_is_own does not work correctly with the use case of a temporary allocator.
The allocator must be kept around as long as the tensors itself.

Small example:

std::vector<char> buf0;
std::vector<char> buf1;
buf0.resize(...);
buf1.resize(...);
struct ggml_tensor * a = ...;
struct ggml_tensor * b = ...;
struct ggml_allocr * alloc;

alloc = ggml_allocr_new(buf0.data(), buf0.size(), alignment);
ggml_allocr_alloc(alloc, a);
ggml_allocr_free(alloc);

alloc = ggml_allocr_new(buf1.data(), buf1.size(), alignment);
ggml_allocr_alloc(alloc, b);
// Now ggml_allocr_is_own(alloc, a) can be unexpectedly `true`
ggml_allocr_free(alloc);

This results in the allocator freeing tensors that are not actually owned by itself.
I write it 'can happen', but I actually observe this behaviour in train & finetune.
Whether it manifests itself probably depends on malloc.

I can change the train & finetune programs to not free the allocators.
This would solve the problem.

But in the above example it still is a bit weird, that ggml_allocr_is_own(alloc, a) can unexpectedly return true when the previous allocator was freed.

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Maybe I missed other cases, but this should have been fixed in #4486.

The problem is that checking the addresses doesn't really work with measure allocators. The previous implementation used virtual memory as a stopgap, but this has other problems. Ultimately, the issue is that ggml_allocr_new creates a temporary ggml_backend_buffer that is freed when the allocator is freed, and from that point these tensors cannot be used anymore since they point to a freed buffer. When using ggml-backend it is possible to free the allocator if you supply your own buffer, but otherwise the ggml-alloc should be kept alive for the lifetime of the tensors.

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Indeed, this solves issues somewhat for finetune. But there are some more cases. I will push PR after I come back from holiday family visit.

}

static bool ggml_is_view(struct ggml_tensor * t) {
return t->view_src != NULL;
}

void ggml_allocr_alloc(struct ggml_allocr * alloc, struct ggml_tensor * tensor) {
#ifdef GGML_ALLOCATOR_DEBUG
GGML_ASSERT(!ggml_is_view(tensor)); // views generally get data pointer from one of their sources
GGML_ASSERT(tensor->data == NULL); // avoid allocating tensor which already has memory allocated
#endif
size_t size = ggml_allocr_get_alloc_size(alloc, tensor);

size_t size = ggml_backend_buffer_get_alloc_size(alloc->buffer, tensor);
size = aligned_offset(NULL, size, alloc->alignment);

AT_PRINTF("%s: allocating %s (%zu bytes) - ", __func__, tensor->name, size);
Expand Down Expand Up @@ -188,6 +163,8 @@ void ggml_allocr_alloc(struct ggml_allocr * alloc, struct ggml_tensor * tensor)

tensor->data = addr;
AT_PRINTF("%s: allocated data at %p\n", __func__, tensor->data);
tensor->buffer = alloc->buffer;
ggml_backend_buffer_init_tensor(alloc->buffer, tensor);

#ifdef GGML_ALLOCATOR_DEBUG
add_allocated_tensor(alloc, tensor);
Expand All @@ -208,19 +185,21 @@ void ggml_allocr_alloc(struct ggml_allocr * alloc, struct ggml_tensor * tensor)

// this is a very naive implementation, but for our case the number of free blocks should be very small
static void ggml_allocr_free_tensor(struct ggml_allocr * alloc, struct ggml_tensor * tensor) {
void * ptr = tensor->data;

if (ggml_allocr_is_own(alloc, tensor) == false) {
// the tensor was not allocated in this buffer
// this can happen because the graph allocator will try to free weights and other tensors from different buffers
// the easiest way to deal with this is just to ignore it
AT_PRINTF("ignoring %s (their buffer: %p, our buffer: %p)\n", tensor->name, (void *)tensor->buffer, (void *)alloc->buffer);
return;
}

size_t size = ggml_allocr_get_alloc_size(alloc, tensor);
void * ptr = tensor->data;

size_t size = ggml_backend_buffer_get_alloc_size(alloc->buffer, tensor);
size = aligned_offset(NULL, size, alloc->alignment);
AT_PRINTF("%s: freeing %s at %p (%zu bytes) - n_free_blocks = %d\n", __func__, tensor->name, ptr, size, alloc->n_free_blocks);
AT_PRINTF("%s: alloc->data = %p alloc->data+alloc->size = %p alloc->data+alloc->max_size = %p\n", __func__, alloc->data, (char*)alloc->data + alloc->size, (char*)alloc->data + alloc->max_size);

ggml_backend_buffer_free_tensor(alloc->buffer, tensor);

#ifdef GGML_ALLOCATOR_DEBUG
remove_allocated_tensor(alloc, tensor);
Expand Down Expand Up @@ -285,15 +264,18 @@ void ggml_allocr_reset(struct ggml_allocr * alloc) {
alloc->n_free_blocks = 1;
size_t align_offset = aligned_offset(alloc->data, 0, alloc->alignment);
alloc->free_blocks[0].addr = (char *)alloc->data + align_offset;
alloc->free_blocks[0].size = alloc->size - align_offset;
alloc->free_blocks[0].size = ggml_backend_buffer_get_size(alloc->buffer) - align_offset;
}

struct ggml_allocr * ggml_allocr_new(void * data, size_t size, size_t alignment) {
struct ggml_allocr * alloc = (struct ggml_allocr *)malloc(sizeof(struct ggml_allocr) /* + n_free_blocks * sizeof(struct free_block) */);
struct ggml_backend_buffer * buffer = ggml_backend_cpu_buffer_from_ptr(NULL, data, size);

struct ggml_allocr * alloc = (struct ggml_allocr *)malloc(sizeof(struct ggml_allocr));

*alloc = (struct ggml_allocr){
/*.data = */ data,
/*.size = */ size,
/*.buffer = */ buffer,
/*.buffer_owned = */ true,
/*.base = */ ggml_backend_buffer_get_base(buffer),
/*.alignment = */ alignment,
/*.n_free_blocks = */ 0,
/*.free_blocks = */ {{0}},
Expand All @@ -312,74 +294,26 @@ struct ggml_allocr * ggml_allocr_new(void * data, size_t size, size_t alignment)
return alloc;
}

// OS specific functions to allocate and free uncommitted virtual memory
static void * alloc_vmem(size_t size) {
#if defined(_WIN32)
return VirtualAlloc(NULL, size, MEM_RESERVE, PAGE_NOACCESS);
#elif defined(_POSIX_MAPPED_FILES)
void * ptr = mmap(NULL, size, PROT_NONE, MAP_PRIVATE | MAP_ANON, -1, 0);
if (ptr == MAP_FAILED) {
return NULL;
}
return ptr;
#else
// use a fixed address for other platforms
uintptr_t base_addr = (uintptr_t)-size - 0x100;
return (void *)base_addr;
#endif
}

static void free_vmem(void * base_addr, size_t size) {
#if defined(_WIN32)
VirtualFree(base_addr, 0, MEM_RELEASE);
UNUSED(size);
#elif defined(_POSIX_MAPPED_FILES)
munmap(base_addr, size);
#else
// nothing to do
UNUSED(base_addr);
UNUSED(size);
#endif
}

// allocate uncommitted virtual memory to measure the size of the graph
static void alloc_measure_vmem(void ** base_addr, size_t * size) {
// 128GB for 64-bit, 1GB for 32-bit
*size = sizeof(void *) == 4 ? 1ULL<<30 : 1ULL<<37;
do {
*base_addr = alloc_vmem(*size);
if (*base_addr != NULL) {
AT_PRINTF("allocated %.2f GB of virtual memory for measure buffer at %p\n", *size / 1024.0 / 1024.0 / 1024.0, *base_addr);
return;
}
// try again with half the size
*size /= 2;
} while (*size > 0);

GGML_ASSERT(!"failed to allocate virtual memory for measure buffer");
}

static void free_measure_vmem(void * base_addr, size_t size) {
free_vmem(base_addr, size);
}

struct ggml_allocr * ggml_allocr_new_measure(size_t alignment) {
struct ggml_allocr * alloc = (struct ggml_allocr *)malloc(sizeof(struct ggml_allocr) /* + n_free_blocks * sizeof(struct free_block) */);
struct ggml_allocr * alloc = ggml_allocr_new((void *)0x1000, (size_t)-0x1001, alignment);
alloc->measure = true;

void * base_addr;
size_t size;
return alloc;
}

alloc_measure_vmem(&base_addr, &size);
struct ggml_allocr * ggml_allocr_new_from_buffer(struct ggml_backend_buffer * buffer) {
struct ggml_allocr * alloc = (struct ggml_allocr *)malloc(sizeof(struct ggml_allocr));

*alloc = (struct ggml_allocr){
/*.data = */ base_addr,
/*.size = */ size,
/*.alignment = */ alignment,
/*.buffer = */ buffer,
/*.buffer_owned = */ false,
/*.base = */ ggml_backend_buffer_get_base(buffer),
/*.alignment = */ ggml_backend_buffer_get_alignment(buffer),
/*.n_free_blocks = */ 0,
/*.free_blocks = */ {{0}},
/*.hash_table = */ {{0}},
/*.max_size = */ 0,
/*.measure = */ true,
/*.measure = */ false,
/*.parse_seq = */ {0},
/*.parse_seq_len = */ 0,
#ifdef GGML_ALLOCATOR_DEBUG
Expand All @@ -393,8 +327,8 @@ struct ggml_allocr * ggml_allocr_new_measure(size_t alignment) {
}

void ggml_allocr_free(struct ggml_allocr * alloc) {
if (alloc->measure) {
free_measure_vmem(alloc->data, alloc->size);
if (alloc->buffer_owned) {
ggml_backend_buffer_free(alloc->buffer);
}
free(alloc);
}
Expand Down Expand Up @@ -437,20 +371,30 @@ static bool ggml_op_can_inplace(enum ggml_op op) {
case GGML_OP_ROPE:
case GGML_OP_RMS_NORM:
case GGML_OP_SOFT_MAX:
case GGML_OP_CONT:
return true;

default:
return false;
}
}

static void init_view(struct ggml_allocr * alloc, struct ggml_tensor * view) {
assert(view->view_src != NULL && view->view_src->data != NULL);
view->backend = view->view_src->backend;
view->buffer = view->view_src->buffer;
view->data = (char *)view->view_src->data + view->view_offs;

// FIXME: the view should be initialized by the owning buffer, but currently this breaks the CUDA backend
// due to the ggml_tensor_extra_gpu ring buffer overwriting the KV cache extras
assert(ggml_allocr_is_measure(alloc) || view->buffer->backend == alloc->buffer->backend);
ggml_backend_buffer_init_tensor(alloc->buffer, view);
}

static void allocate_node(struct ggml_allocr * alloc, struct ggml_tensor * node) {
struct hash_node * ht = alloc->hash_table;
if (node->data == NULL) {
if (ggml_is_view(node)) {
assert(node->view_src->data != NULL);
node->data = (char *)node->view_src->data + node->view_offs;
init_view(alloc, node);
} else {
// see if we can reuse a parent's buffer (inplace)
if (ggml_op_can_inplace(node->op)) {
Expand Down Expand Up @@ -478,13 +422,17 @@ static void allocate_node(struct ggml_allocr * alloc, struct ggml_tensor * node)
// adding a view_src pointer to the tensor would solve this and simplify the code dealing with views
// for now, we only reuse the parent's data if the offset is zero (view_src->data == parent->data)
AT_PRINTF("reusing view parent %s (%s) for %s\n", parent->name, view_src->name, node->name);
node->data = parent->data;
node->view_src = view_src;
view_src_hn->n_views += 1;
init_view(alloc, node);
return;
}
}
else {
AT_PRINTF("reusing parent %s for %s\n", parent->name, node->name);
node->data = parent->data;
node->view_src = parent;
p_hn->n_views += 1;
init_view(alloc, node);
return;
}
}
Expand All @@ -495,7 +443,7 @@ static void allocate_node(struct ggml_allocr * alloc, struct ggml_tensor * node)
}
}

static size_t ggml_allocr_alloc_graph_tensors_n(
size_t ggml_allocr_alloc_graph_n(
struct ggml_allocr * alloc,
struct ggml_cgraph ** graphs, int n_graphs,
struct ggml_tensor *** inputs, struct ggml_tensor *** outputs) {
Expand All @@ -513,6 +461,10 @@ static size_t ggml_allocr_alloc_graph_tensors_n(
if (ggml_is_view(node)) {
struct ggml_tensor * view_src = node->view_src;
hash_get(ht, view_src)->n_views += 1;
if (node->buffer == NULL && node->data != NULL) {
// view of a pre-allocated tensor, didn't call init_view() yet
init_view(alloc, node);
}
}

for (int j = 0; j < GGML_MAX_SRC; j++) {
Expand All @@ -521,6 +473,9 @@ static size_t ggml_allocr_alloc_graph_tensors_n(
break;
}
hash_get(ht, parent)->n_children += 1;
if (ggml_is_view(parent) && parent->buffer == NULL && parent->data != NULL) {
init_view(alloc, parent);
}
}
}
}
Expand Down Expand Up @@ -631,7 +586,7 @@ static size_t ggml_allocr_alloc_graph_tensors_n(
}

size_t ggml_allocr_alloc_graph(struct ggml_allocr * alloc, struct ggml_cgraph * graph) {
return ggml_allocr_alloc_graph_tensors_n(alloc, &graph, 1, NULL, NULL);
return ggml_allocr_alloc_graph_n(alloc, &graph, 1, NULL, NULL);
}

size_t ggml_allocr_max_size(struct ggml_allocr * alloc) {
Expand Down
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