Support calling mlock() on loaded model data on Linux and macOS (#453)

* Support calling mlock() on loaded model data on Linux and macOS

This is enabled by a new --mlock command line option.

Using mlock() disables swapping and memory compression for the model
data.  Doing so can be useful on systems where the model takes up a
large fraction of system RAM.  In my experience, macOS is quite eager to
start compressing llama.cpp's memory, which then makes it halt for a few
seconds while it decompresses, even with a model that uses "only" 25GB
out of 32GB.

Of course, this comes at the cost of forcing the system to swap or
compress other processes' memory instead, so it needs to be used with
care and shouldn't be enabled by default.

In theory it should be possible to support this on Windows as well using
VirtualLock(), but I'm not much of a Windows user.

* Update llama.cpp

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
This commit is contained in:
comex 2023-03-24 08:19:05 -07:00 committed by GitHub
parent 8d4a855c24
commit 563cdc391d
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GPG key ID: 4AEE18F83AFDEB23
7 changed files with 91 additions and 12 deletions

76
ggml.c
View file

@ -1,5 +1,5 @@
// Defines CLOCK_MONOTONIC on Linux
#define _POSIX_C_SOURCE 199309L
// Defines CLOCK_MONOTONIC and asprintf on Linux
#define _GNU_SOURCE
#include "ggml.h"
@ -10,6 +10,7 @@
#endif
#include <assert.h>
#include <errno.h>
#include <time.h>
#include <math.h>
#include <stdlib.h>
@ -31,7 +32,6 @@
#else
// ref: https://github.com/ggerganov/whisper.cpp/issues/168
#include <windows.h>
#include <errno.h>
#endif
typedef volatile LONG atomic_int;
@ -83,6 +83,17 @@ typedef void* thread_ret_t;
#define static_assert(cond, msg) _Static_assert(cond, msg)
#endif
#define GGML_MLOCK_SUPPORT 0
#ifdef __has_include
#if __has_include(<sys/mman.h>)
#undef GGML_MLOCK_SUPPORT
#define GGML_MLOCK_SUPPORT 1
#include <sys/mman.h>
#endif
#endif
/*#define GGML_PERF*/
#define GGML_DEBUG 0
#define GGML_GELU_FP16
@ -2344,6 +2355,7 @@ struct ggml_context {
size_t mem_size;
void * mem_buffer;
bool mem_buffer_owned;
bool mem_buffer_mlocked;
int n_objects;
@ -2619,16 +2631,19 @@ struct ggml_context * ggml_init(struct ggml_init_params params) {
}
*ctx = (struct ggml_context) {
/*.mem_size =*/ params.mem_size,
/*.mem_buffer =*/ params.mem_buffer ? params.mem_buffer : malloc(params.mem_size),
/*.mem_buffer_owned =*/ params.mem_buffer ? false : true,
/*.n_objects =*/ 0,
/*.objects_begin =*/ NULL,
/*.objects_end =*/ NULL,
/*.scratch =*/ { 0, 0, NULL, },
/*.scratch_save =*/ { 0, 0, NULL, },
/*.mem_size =*/ params.mem_size,
/*.mem_buffer =*/ params.mem_buffer ? params.mem_buffer : malloc(params.mem_size),
/*.mem_buffer_owned =*/ params.mem_buffer ? false : true,
/*.mem_buffer_mlocked =*/ false,
/*.n_objects =*/ 0,
/*.objects_begin =*/ NULL,
/*.objects_end =*/ NULL,
/*.scratch =*/ { 0, 0, NULL, },
/*.scratch_save =*/ { 0, 0, NULL, },
};
GGML_ASSERT(ctx->mem_buffer != NULL); // check for allocation failure
ggml_assert_aligned(ctx->mem_buffer);
GGML_PRINT_DEBUG("%s: context initialized\n", __func__);
@ -2651,6 +2666,14 @@ void ggml_free(struct ggml_context * ctx) {
GGML_PRINT_DEBUG("%s: context %d with %d objects has been freed. memory used = %zu\n",
__func__, i, ctx->n_objects, ctx->objects_end->offs + ctx->objects_end->size);
#if GGML_MLOCK_SUPPORT
if (ctx->mem_buffer_mlocked) {
if (munlock(ctx->mem_buffer, ctx->mem_size)) {
fprintf(stderr, "%s: failed to munlock buffer: %s\n", __func__, strerror(errno));
}
}
#endif
if (ctx->mem_buffer_owned) {
free(ctx->mem_buffer);
}
@ -2679,6 +2702,37 @@ size_t ggml_set_scratch(struct ggml_context * ctx, struct ggml_scratch scratch)
return result;
}
bool ggml_mlock_supported(void) {
return GGML_MLOCK_SUPPORT;
}
#if GGML_MLOCK_SUPPORT
#ifdef __APPLE__
#define MLOCK_SUGGESTION "Try increasing the sysctl values 'vm.user_wire_limit' and 'vm.global_user_wire_limit' and/or\n" \
"decreasing 'vm.global_no_user_wire_amount'. Also try increasing RLIMIT_MLOCK (ulimit -l)."
#else
#define MLOCK_SUGGESTION "Try increasing RLIMIT_MLOCK (ulimit -l)."
#endif
bool ggml_mlock(struct ggml_context * ctx, char ** err_p) {
if (ctx->mem_buffer_mlocked) {
return true;
}
if (mlock(ctx->mem_buffer, ctx->mem_size)) {
int ret = asprintf(err_p, "failed to mlock %zu-byte buffer: %s\n" MLOCK_SUGGESTION,
ctx->mem_size, strerror(errno));
GGML_ASSERT(ret >= 0);
return false;
}
ctx->mem_buffer_mlocked = true;
return true;
}
#else // GGML_MLOCK_SUPPORT
bool ggml_mlock(struct ggml_context * ctx, char ** err_p) {
*err_p = strdup("can't mlock because it's not supported on this system");
return false;
}
#endif // GGML_MLOCK_SUPPORT
////////////////////////////////////////////////////////////////////////////////
struct ggml_tensor * ggml_new_tensor_impl(

3
ggml.h
View file

@ -343,6 +343,9 @@ size_t ggml_used_mem(const struct ggml_context * ctx);
size_t ggml_set_scratch(struct ggml_context * ctx, struct ggml_scratch scratch);
bool ggml_mlock_supported(void);
bool ggml_mlock(struct ggml_context * ctx, char ** err_p);
struct ggml_tensor * ggml_new_tensor(
struct ggml_context * ctx,
enum ggml_type type,

View file

@ -115,6 +115,7 @@ struct llama_context_params llama_context_default_params() {
/*.f16_kv =*/ false,
/*.logits_all =*/ false,
/*.vocab_only =*/ false,
/*.use_mlock =*/ false,
/*.embedding =*/ false,
};
@ -1428,11 +1429,22 @@ struct llama_context * llama_init_from_file(
ggml_type type_memory = params.f16_kv ? GGML_TYPE_F16 : GGML_TYPE_F32;
if (!llama_model_load(path_model, *ctx, params.n_ctx, params.n_parts, type_memory, params.vocab_only)) {
if (!llama_model_load(path_model, *ctx, params.n_ctx, params.n_parts, type_memory,
params.vocab_only)) {
fprintf(stderr, "%s: failed to load model\n", __func__);
delete ctx;
return nullptr;
}
if (params.use_mlock) {
char *err;
if (!ggml_mlock(ctx->model.ctx, &err)) {
fprintf(stderr, "%s\n", err);
free(err);
delete ctx;
return nullptr;
}
}
// reserve memory for context buffers
{

View file

@ -53,6 +53,7 @@ extern "C" {
bool f16_kv; // use fp16 for KV cache
bool logits_all; // the llama_eval() call computes all logits, not just the last one
bool vocab_only; // only load the vocabulary, no weights
bool use_mlock; // force system to keep model in RAM
bool embedding; // embedding mode only
};

View file

@ -199,6 +199,7 @@ int main(int argc, char ** argv) {
lparams.seed = params.seed;
lparams.f16_kv = params.memory_f16;
lparams.logits_all = params.perplexity;
lparams.use_mlock = params.use_mlock;
lparams.embedding = params.embedding;
ctx = llama_init_from_file(params.model.c_str(), lparams);

View file

@ -1,3 +1,5 @@
#include "ggml.h"
#include "utils.h"
#include <cassert>
@ -127,6 +129,8 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
params.instruct = true;
} else if (arg == "--color") {
params.use_color = true;
} else if (arg == "--mlock") {
params.use_mlock = true;
} else if (arg == "-r" || arg == "--reverse-prompt") {
if (++i >= argc) {
invalid_param = true;
@ -194,6 +198,9 @@ void gpt_print_usage(int /*argc*/, char ** argv, const gpt_params & params) {
fprintf(stderr, " --n_parts N number of model parts (default: -1 = determine from dimensions)\n");
fprintf(stderr, " -b N, --batch_size N batch size for prompt processing (default: %d)\n", params.n_batch);
fprintf(stderr, " --perplexity compute perplexity over the prompt\n");
if (ggml_mlock_supported()) {
fprintf(stderr, " --mlock force system to keep model in RAM rather than swapping or compressing\n");
}
fprintf(stderr, " -m FNAME, --model FNAME\n");
fprintf(stderr, " model path (default: %s)\n", params.model.c_str());
fprintf(stderr, "\n");

View file

@ -46,6 +46,7 @@ struct gpt_params {
bool instruct = false; // instruction mode (used for Alpaca models)
bool ignore_eos = false; // do not stop generating after eos
bool perplexity = false; // compute perplexity over the prompt
bool use_mlock = false; // use mlock to keep model in memory
};
bool gpt_params_parse(int argc, char ** argv, gpt_params & params);