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add --no-mmap in llama-bench (#5257)

Browse Source 
* add --no-mmap, show sycl backend

* fix conflict

* fix code format, change print for --no-mmap

* ren no_mmap to mmap, show mmap when not default value in printer

* update guide for mmap

* mv position to reduce model reload
This commit is contained in:
Neo Zhang Jianyu 2024-02-02 03:48:53 +08:00 committed by GitHub
parent 4d0924a890
commit 128dcbd3c9
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4 changed files with 89 additions and 10 deletions
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2
README-sycl.md
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@ -405,7 +405,7 @@ Using device **0** (Intel(R) Arc(TM) A770 Graphics) as main device
llama.cpp use mmap as default way to read model file and copy to GPU. In some system, memcpy will be abnormal and block.
Solution: add **--no-mmap**.
Solution: add **--no-mmap** or **--mmap 0**.
## Q&A

60
examples/llama-bench/llama-bench.cpp
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@ -20,6 +20,7 @@
#include "llama.h"
#include "common.h"
#include "ggml-cuda.h"
#include "ggml-sycl.h"
// utils
static uint64_t get_time_ns() {
@ -120,6 +121,22 @@ static std::string get_gpu_info() {
id += "/";
}
}
#endif
#ifdef GGML_USE_SYCL
int device_list[GGML_SYCL_MAX_DEVICES];
ggml_sycl_get_gpu_list(device_list, GGML_SYCL_MAX_DEVICES);
for (int i = 0; i < GGML_SYCL_MAX_DEVICES; i++) {
if (device_list[i] >0 ){
char buf[128];
ggml_sycl_get_device_description(i, buf, sizeof(buf));
id += buf;
id += "/";
}
}
if (id.length() >2 ) {
id.pop_back();
}
#endif
// TODO: other backends
return id;
@ -161,6 +178,7 @@ struct cmd_params {
std::vector<bool> no_kv_offload;
std::vector<bool> mul_mat_q;
std::vector<std::vector<float>> tensor_split;
std::vector<bool> use_mmap;
int reps;
bool verbose;
output_formats output_format;
@ -180,6 +198,7 @@ static const cmd_params cmd_params_defaults = {
/* no_kv_offload */ {false},
/* mul_mat_q */ {true},
/* tensor_split */ {std::vector<float>(llama_max_devices(), 0.0f)},
/* use_mmap */ {true},
/* reps */ 5,
/* verbose */ false,
/* output_format */ MARKDOWN
@ -201,6 +220,7 @@ static void print_usage(int /* argc */, char ** argv) {
printf(" -sm, --split-mode <none|layer|row> (default: %s)\n", join(transform_to_str(cmd_params_defaults.split_mode, split_mode_str), ",").c_str());
printf(" -mg, --main-gpu <i> (default: %s)\n", join(cmd_params_defaults.main_gpu, ",").c_str());
printf(" -nkvo, --no-kv-offload <0|1> (default: %s)\n", join(cmd_params_defaults.no_kv_offload, ",").c_str());
printf(" -mmp, --mmap <0|1> (default: %s)\n", join(cmd_params_defaults.use_mmap, ",").c_str());
printf(" -mmq, --mul-mat-q <0|1> (default: %s)\n", join(cmd_params_defaults.mul_mat_q, ",").c_str());
printf(" -ts, --tensor_split <ts0/ts1/..> (default: 0)\n");
printf(" -r, --repetitions <n> (default: %d)\n", cmd_params_defaults.reps);
@ -370,6 +390,13 @@ static cmd_params parse_cmd_params(int argc, char ** argv) {
}
auto p = split<bool>(argv[i], split_delim);
params.mul_mat_q.insert(params.mul_mat_q.end(), p.begin(), p.end());
} else if (arg == "-mmp" || arg == "--mmap") {
if (++i >= argc) {
invalid_param = true;
break;
}
auto p = split<bool>(argv[i], split_delim);
params.use_mmap.insert(params.use_mmap.end(), p.begin(), p.end());
} else if (arg == "-ts" || arg == "--tensor-split") {
if (++i >= argc) {
invalid_param = true;
@ -441,6 +468,7 @@ static cmd_params parse_cmd_params(int argc, char ** argv) {
if (params.no_kv_offload.empty()){ params.no_kv_offload = cmd_params_defaults.no_kv_offload; }
if (params.mul_mat_q.empty()) { params.mul_mat_q = cmd_params_defaults.mul_mat_q; }
if (params.tensor_split.empty()) { params.tensor_split = cmd_params_defaults.tensor_split; }
if (params.use_mmap.empty()) { params.use_mmap = cmd_params_defaults.use_mmap; }
if (params.n_threads.empty()) { params.n_threads = cmd_params_defaults.n_threads; }
return params;
@ -460,6 +488,7 @@ struct cmd_params_instance {
bool no_kv_offload;
bool mul_mat_q;
std::vector<float> tensor_split;
bool use_mmap;
llama_model_params to_llama_mparams() const {
llama_model_params mparams = llama_model_default_params();
@ -468,6 +497,7 @@ struct cmd_params_instance {
mparams.split_mode = split_mode;
mparams.main_gpu = main_gpu;
mparams.tensor_split = tensor_split.data();
mparams.use_mmap = use_mmap;
return mparams;
}
@ -477,6 +507,7 @@ struct cmd_params_instance {
n_gpu_layers == other.n_gpu_layers &&
split_mode == other.split_mode &&
main_gpu == other.main_gpu &&
use_mmap == other.use_mmap &&
tensor_split == other.tensor_split;
}
@ -503,6 +534,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
for (const auto & sm : params.split_mode)
for (const auto & mg : params.main_gpu)
for (const auto & ts : params.tensor_split)
for (const auto & mmp : params.use_mmap)
for (const auto & nb : params.n_batch)
for (const auto & tk : params.type_k)
for (const auto & tv : params.type_v)
@ -527,6 +559,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .no_kv_offload= */ nkvo,
/* .mul_mat_q = */ mmq,
/* .tensor_split = */ ts,
/* .use_mmap = */ mmp,
};
instances.push_back(instance);
}
@ -549,6 +582,7 @@ static std::vector<cmd_params_instance> get_cmd_params_instances(const cmd_param
/* .no_kv_offload= */ nkvo,
/* .mul_mat_q = */ mmq,
/* .tensor_split = */ ts,
/* .use_mmap = */ mmp,
};
instances.push_back(instance);
}
@ -565,6 +599,7 @@ struct test {
static const bool vulkan;
static const bool kompute;
static const bool metal;
static const bool sycl;
static const bool gpu_blas;
static const bool blas;
static const std::string cpu_info;
@ -583,6 +618,7 @@ struct test {
bool no_kv_offload;
bool mul_mat_q;
std::vector<float> tensor_split;
bool use_mmap;
int n_prompt;
int n_gen;
std::string test_time;
@ -605,6 +641,7 @@ struct test {
no_kv_offload = inst.no_kv_offload;
mul_mat_q = inst.mul_mat_q;
tensor_split = inst.tensor_split;
use_mmap = inst.use_mmap;
n_prompt = inst.n_prompt;
n_gen = inst.n_gen;
// RFC 3339 date-time format
@ -654,25 +691,29 @@ struct test {
if (metal) {
return "Metal";
}
if (sycl) {
return GGML_SYCL_NAME;
}
if (gpu_blas) {
return "GPU BLAS";
}
if (blas) {
return "BLAS";
}
return "CPU";
}
static const std::vector<std::string> & get_fields() {
static const std::vector<std::string> fields = {
"build_commit", "build_number",
"cuda", "opencl", "vulkan", "kompute", "metal", "gpu_blas", "blas",
"cuda", "opencl", "vulkan", "kompute", "metal", "sycl", "gpu_blas", "blas",
"cpu_info", "gpu_info",
"model_filename", "model_type", "model_size", "model_n_params",
"n_batch", "n_threads", "type_k", "type_v",
"n_gpu_layers", "split_mode",
"main_gpu", "no_kv_offload",
"mul_mat_q", "tensor_split",
"mul_mat_q", "tensor_split", "use_mmap",
"n_prompt", "n_gen", "test_time",
"avg_ns", "stddev_ns",
"avg_ts", "stddev_ts"
@ -691,8 +732,8 @@ struct test {
return INT;
}
if (field == "cuda" || field == "opencl" || field == "vulkan" || field == "kompute" || field == "metal" ||
field == "gpu_blas" || field == "blas" || field == "f16_kv" || field == "no_kv_offload" ||
field == "mul_mat_q") {
field == "gpu_blas" || field == "blas" || field == "sycl" ||field == "f16_kv" || field == "no_kv_offload" ||
field == "mul_mat_q" || field == "use_mmap") {
return BOOL;
}
if (field == "avg_ts" || field == "stddev_ts") {
@ -720,13 +761,13 @@ struct test {
std::vector<std::string> values = {
build_commit, std::to_string(build_number),
std::to_string(cuda), std::to_string(opencl), std::to_string(vulkan), std::to_string(vulkan),
std::to_string(metal), std::to_string(gpu_blas), std::to_string(blas),
std::to_string(metal), std::to_string(sycl), std::to_string(gpu_blas), std::to_string(blas),
cpu_info, gpu_info,
model_filename, model_type, std::to_string(model_size), std::to_string(model_n_params),
std::to_string(n_batch), std::to_string(n_threads), ggml_type_name(type_k), ggml_type_name(type_v),
std::to_string(n_gpu_layers), split_mode_str(split_mode),
std::to_string(main_gpu), std::to_string(no_kv_offload),
std::to_string(mul_mat_q), tensor_split_str,
std::to_string(mul_mat_q), tensor_split_str, std::to_string(use_mmap),
std::to_string(n_prompt), std::to_string(n_gen), test_time,
std::to_string(avg_ns()), std::to_string(stdev_ns()),
std::to_string(avg_ts()), std::to_string(stdev_ts())
@ -753,6 +794,7 @@ const bool test::kompute = !!ggml_cpu_has_kompute();
const bool test::metal = !!ggml_cpu_has_metal();
const bool test::gpu_blas = !!ggml_cpu_has_gpublas();
const bool test::blas = !!ggml_cpu_has_blas();
const bool test::sycl = !!ggml_cpu_has_sycl();
const std::string test::cpu_info = get_cpu_info();
const std::string test::gpu_info = get_gpu_info();
@ -895,6 +937,9 @@ struct markdown_printer : public printer {
if (field == "no_kv_offload") {
return "nkvo";
}
if (field == "use_mmap") {
return "mmap";
}
if (field == "tensor_split") {
return "ts";
}
@ -938,6 +983,9 @@ struct markdown_printer : public printer {
if (params.tensor_split.size() > 1 || params.tensor_split != cmd_params_defaults.tensor_split) {
fields.push_back("tensor_split");
}
if (params.use_mmap.size() > 1 || params.use_mmap != cmd_params_defaults.use_mmap) {
fields.push_back("use_mmap");
}
fields.push_back("test");
fields.push_back("t/s");

34
ggml-sycl.cpp
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@ -2928,7 +2928,6 @@ void ggml_sycl_set_main_device(int main_device);
void ggml_sycl_set_mul_mat_q(bool mul_mat_q);
void ggml_sycl_set_scratch_size(size_t scratch_size);
void ggml_sycl_free_scratch(void);
int ggml_sycl_get_device_count(void);
void ggml_sycl_get_device_description(int device, char * description, size_t description_size);
bool ggml_backend_is_sycl(ggml_backend_t backend);
int ggml_backend_sycl_get_device(ggml_backend_t backend);
@ -14493,6 +14492,37 @@ bool ggml_sycl_compute_forward(struct ggml_compute_params * params, struct ggml_
return true;
}
GGML_API GGML_CALL void ggml_sycl_get_gpu_list(int *id_list, int max_len) try {
int max_compute_units = -1;
for(int i=0;i<max_len;i++) id_list[i] = 0;
int device_count = dpct::dev_mgr::instance().device_count();
for(int id=0; id< device_count; id++){
sycl::device device = dpct::dev_mgr::instance().get_device(id);
if (!device.is_gpu()) continue;
dpct::device_info prop;
dpct::get_device_info(prop, device);
if(max_compute_units < prop.get_max_compute_units()) max_compute_units = prop.get_max_compute_units();
}
for(int id=0;id< device_count;id++){
sycl::device device = dpct::dev_mgr::instance().get_device(id);
if (!device.is_gpu()) continue;
dpct::device_info prop;
dpct::get_device_info(prop, device);
if(max_compute_units == prop.get_max_compute_units() && prop.get_major_version() == 1 ){
id_list[id] = 1;
}
}
return;
}
catch (sycl::exception const &exc) {
std::cerr << exc.what() << "Exception caught at file:" << __FILE__
<< ", line:" << __LINE__ << std::endl;
std::exit(1);
}
int ggml_sycl_get_device_count() try {
int device_count;
if (CHECK_TRY_ERROR(device_count =
@ -14507,7 +14537,7 @@ catch (sycl::exception const &exc) {
std::exit(1);
}
void ggml_sycl_get_device_description(int device, char *description,
GGML_API GGML_CALL void ggml_sycl_get_device_description(int device, char *description,
size_t description_size) try {
dpct::device_info prop;
SYCL_CHECK(CHECK_TRY_ERROR(dpct::get_device_info(

3
ggml-sycl.h
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@ -22,7 +22,8 @@ GGML_API ggml_backend_t ggml_backend_sycl_init(int device);
GGML_API ggml_backend_buffer_type_t ggml_backend_sycl_buffer_type(int device);
GGML_API ggml_backend_buffer_type_t ggml_backend_sycl_host_buffer_type(void);
GGML_API void ggml_backend_sycl_print_sycl_devices(void);
GGML_API GGML_CALL void ggml_sycl_get_gpu_list(int *id_list, int max_len);
GGML_API GGML_CALL void ggml_sycl_get_device_description(int device, char *description, size_t description_size);
#ifdef __cplusplus
}
#endif