Merge bcc7f8b6bf into 1f48b0abcf

examples/common.cpp

@@ -91,6 +91,7 @@ void process_escapes(std::string& input) {
 }
 
 bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
+    bool ethreads_set = false;
     bool invalid_param = false;
     bool escape_prompt = false;
     std::string arg;
@@ -114,6 +115,13 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
                 break;
             }
             params.n_threads = std::stoi(argv[i]);
+        } else if (arg == "-e" || arg == "--eval-threads") {
+            if (++i >= argc) {
+                invalid_param = true;
+                break;
+            }
+            params.n_ethreads = std::stoi(argv[i]);
+            ethreads_set = true;
         } else if (arg == "-p" || arg == "--prompt") {
             if (++i >= argc) {
                 invalid_param = true;
@@ -339,6 +347,12 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
             exit(1);
         }
     }
+
+    // ensure that n_ethreads defaults to the system thread-max only when n_threads is not set
+    if (!ethreads_set) {
+        params.n_ethreads = params.n_threads;
+    }
+
     if (invalid_param) {
         fprintf(stderr, "error: invalid parameter for argument: %s\n", arg.c_str());
         gpt_print_usage(argc, argv, default_params);

examples/common.h

@@ -18,6 +18,7 @@ int32_t get_num_physical_cores();
 struct gpt_params {
     int32_t seed          = -1;   // RNG seed
     int32_t n_threads     = get_num_physical_cores();
+    int32_t n_ethreads    = get_num_physical_cores();
     int32_t n_predict     = -1;  // new tokens to predict
     int32_t n_parts       = -1;   // amount of model parts (-1 = determine from model dimensions)
     int32_t n_ctx         = 512;  // context size

examples/embedding/embedding.cpp

@@ -71,7 +71,7 @@ int main(int argc, char ** argv) {
 
     if (params.embedding){
         if (embd_inp.size() > 0) {
-            if (llama_eval(ctx, embd_inp.data(), embd_inp.size(), n_past, params.n_threads)) {
+            if (llama_eval(ctx, embd_inp.data(), embd_inp.size(), n_past, params.n_threads, params.n_ethreads)) {
                 fprintf(stderr, "%s : failed to eval\n", __func__);
                 return 1;
             }

examples/main/main.cpp

@@ -123,12 +123,12 @@ int main(int argc, char ** argv) {
     if (params.mem_test) {
         {
             const std::vector<llama_token> tmp(params.n_batch, 0);
-            llama_eval(ctx, tmp.data(), tmp.size(), 0, params.n_threads);
+            llama_eval(ctx, tmp.data(), tmp.size(), 0, params.n_threads, params.n_ethreads);
         }
 
         {
             const std::vector<llama_token> tmp = { 0, };
-            llama_eval(ctx, tmp.data(), tmp.size(), params.n_predict - 1, params.n_threads);
+            llama_eval(ctx, tmp.data(), tmp.size(), params.n_predict - 1, params.n_threads, params.n_ethreads);
         }
 
         llama_print_timings(ctx);
@@ -360,7 +360,7 @@ int main(int argc, char ** argv) {
                 if (n_eval > params.n_batch) {
                     n_eval = params.n_batch;
                 }
-                if (llama_eval(ctx, &embd[i], n_eval, n_past, params.n_threads)) {
+                if (llama_eval(ctx, &embd[i], n_eval, n_past, params.n_threads, params.n_ethreads)) {
                     fprintf(stderr, "%s : failed to eval\n", __func__);
                     return 1;
                 }

examples/perplexity/perplexity.cpp

@@ -41,10 +41,11 @@ void perplexity(llama_context * ctx, const gpt_params & params) {
         std::vector<float> logits;
         int num_batches = (params.n_ctx + params.n_batch - 1) / params.n_batch;
         auto start_t = std::chrono::high_resolution_clock::now();
+
         for (int j = 0; j < num_batches; ++j) {
             int batch_start = start + j * params.n_batch;
             int batch_size = std::min(end - batch_start, params.n_batch);
-            if (llama_eval(ctx, tokens.data() + batch_start, batch_size, j * params.n_batch, params.n_threads)) {
+            if (llama_eval(ctx, tokens.data() + batch_start, batch_size, j * params.n_batch, params.n_threads, params.n_ethreads)) {
                 fprintf(stderr, "%s : failed to eval\n", __func__);
                 return;
             }

llama.cpp

@@ -1045,13 +1045,15 @@ static bool llama_model_load(
 //   - tokens:    new batch of tokens to process
 //   - n_past:    the context size so far
 //   - n_threads: number of threads to use
+//   - n_ethreads: number of threads to use for single-token eval
 //
 static bool llama_eval_internal(
         llama_context & lctx,
     const llama_token * tokens,
             const int   n_tokens,
             const int   n_past,
-            const int   n_threads) {
+            const int   n_threads,
+            const int   n_ethreads) {
     const int64_t t_start_us = ggml_time_us();
 
     const int N = n_tokens;
@@ -1084,7 +1086,7 @@ static bool llama_eval_internal(
     // for big prompts, if BLAS is enabled, it is better to use only one thread
     // otherwise, the threads are spin-lock waiting for the BLAS calls and are degrading the performance
     ggml_cgraph gf = {};
-    gf.n_threads = N >= 32 && ggml_cpu_has_blas() && !ggml_cpu_has_gpublas() ? 1 : n_threads;
+    gf.n_threads = N >= 32 && ggml_cpu_has_blas() && !ggml_cpu_has_gpublas() ? 1 : (N == 1 ? n_ethreads : n_threads);
 
     struct ggml_tensor * embd = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, N);
     ggml_set_name(embd, "embd");
@@ -2722,8 +2724,9 @@ int llama_eval(
            const llama_token * tokens,
                          int   n_tokens,
                          int   n_past,
-                         int   n_threads) {
+                         int   n_threads,
-    if (!llama_eval_internal(*ctx, tokens, n_tokens, n_past, n_threads)) {
+                         int   n_ethreads) {
+    if (!llama_eval_internal(*ctx, tokens, n_tokens, n_past, n_threads, n_ethreads)) {
         fprintf(stderr, "%s: failed to eval\n", __func__);
         return 1;
     }

llama.h

@@ -153,7 +153,8 @@ extern "C" {
                const llama_token * tokens,
                              int   n_tokens,
                              int   n_past,
-                             int   n_threads);
+                             int   n_threads,
+                             int   n_ethreads);
 
     // Convert the provided text into tokens.
     // The tokens pointer must be large enough to hold the resulting tokens.