7 Commits

Author	SHA1	Message	Date
Georgi Gerganov	2b4ea35e56	cuda : add batched cuBLAS GEMM for faster attention (#3749) ... * cmake : add helper for faster CUDA builds * batched : add NGL arg * ggml : skip nops in compute_forward * cuda : minor indentation * cuda : batched cuBLAS GEMMs for src0 F16 and src1 F32 (attention ops) * Apply suggestions from code review These changes plus: ```c++ #define cublasGemmBatchedEx hipblasGemmBatchedEx ``` are needed to compile with ROCM. I haven't done performance testing, but it seems to work. I couldn't figure out how to propose a change for lines outside what the pull changed, also this is the first time trying to create a multi-part review so please forgive me if I mess something up. * cuda : add ROCm / hipBLAS cublasGemmBatchedEx define * cuda : add cublasGemmStridedBatchedEx for non-broadcasted cases * cuda : reduce mallocs in cublasGemmBatchedEx branch * cuda : add TODO for calling cublas from kernel + using mem pool --------- Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>	2023-10-24 16:48:37 +03:00
Marcus Dunn	5be6c803fa	llama : remove token functions with context args in favor of model (#3720) ... * added `llama_model_token_*` variants to all the `llama_token_*` functions. * added `LLAMA_API` * formatting Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * removed old `llama_token` functions * changed 3 more functions to take in model - `llama_token_get_text` - `llama_token_get_score` - `llama_token_get_type` * added back docs * fixed main.cpp * changed token functions to use new model variants * changed token functions to use new model variants --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>	2023-10-23 22:40:03 +03:00
Georgi Gerganov	22c69a2794	batched : add len CLI argument	2023-10-22 08:37:20 +03:00
Georgi Gerganov	0e89203b51	speculative : add tree-based sampling example (#3624) ... * sampling : one sequence per sampling context ggml-ci * speculative : add tree-based sampling support ggml-ci * speculative : reuse the n_parallel CLI param * speculative : refactor sampling * examples : fix build after sampling refactoring ggml-ci * batched : fix n_seq_id * sampling : fix malloc ggml-ci * swift : fix build ggml-ci * swift : try to fix build ggml-ci * prompts : add assistant.txt * common : add llama_batch_add() and llama_batch_clear() helpers * speculative : minor refactor ggml-ci * minor : comments + rename ggml-ci * speculative : fix off-by-one for n_drafted * speculative : fix the n_drafted fix + p constants	2023-10-18 16:21:57 +03:00
Georgi Gerganov	8c70a5ff25	batched : add bench tool (#3545) ... * batched : add bench tool * batched : minor fix table * batched-bench : add readme + n_kv_max is now configurable * batched-bench : init warm-up batch * batched-bench : pass custom set of PP, TG and PL * batched-bench : add mmq CLI arg	2023-10-11 21:25:33 +03:00
slaren	16bc66d947	llama.cpp : split llama_context_params into model and context params (#3301) ... * llama.cpp : split llama_context_params into model and context params ggml-ci * fix metal build * fix freq_base/scale default to model value * llama-bench : keep the same model between tests when possible * move n_threads to llama_context_params, add n_threads_batch * fix mpi build * remove kv_size(), cuda scratch fixes * remove low-vram option * add n_threads_batch to system info, refactor to get_system_info() * add documentation about --threads-batch to the READMEs * llama-bench fix * main : fix rope freq/scale warning * llama.cpp : add llama_get_model common : add llama_tokenize from model * remove duplicated ctx/model functions ggml-ci * cuda : print total VRAM used	2023-09-28 22:42:38 +03:00
Georgi Gerganov	ec893798b7	llama : custom attention mask + parallel decoding + no context swaps (#3228) ... * tests : verify that RoPE is "additive" * llama : replace ggml_diag_mask_inf with ggml_add (custom -inf mask) * ggml : ggml_rope now takes a vector with positions instead of n_past * metal : add rope_f16 kernel + optimize cpy kernels * llama : unified KV cache + batch inference API * llama : add new llama_decode() API that works with llama_batch * llama : add cell_max heuristic for more efficient kv_cache * llama : extend llama_kv_cache API * llama : more robust cell_max heuristic + wip shift * metal : disable concurrency optimization * llama : add llama_kv_cache_shift_seq + no more context swaps * llama : apply K-cache roping for Falcon and Baichuan * speculative : fix KV cache management * parallel : example for serving multiple users in parallel * parallel : disable hot-plug to avoid cache fragmentation * fixes : speculative KV cache + llama worst-case graph * llama : extend batch API to select which logits to output * llama : fix worst case graph build * ggml-cuda : update rope implementation for parallel decoding (#3254) * ggml-cuda : update rope implementation for parallel decoding * better solution for p0 computation * fix rope * simpler rope implementation --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * make : add parallel to build + fix static functions in llama.cpp * simple : fix token counting * parallel : various improvements * llama : fix cell_max logic + rename functions * parallel : try smaller batches when the KV cache is fragmented * parallel : fix sequence termination criteria * llama : silence errors KV cache errors * parallel : remove new line from prompt * parallel : process system prompt once + configurable paramters + llama API * parallel : remove question with short answers * parallel : count cache misses * parallel : print misses on each request * parallel : minor * llama : fix n_kv to never become 0 * parallel : rename hot-plug to continuous-batching * llama : improve llama_batch API + simplify parallel example * simple : add parallel decoding support * simple : improve comments + free batch * ggml-cuda : add rope f16, restore performance with parallel decoding (#3272) * ggml-cuda : add rope f16, restore performance * offload KQ_mask with all models * fix rope shift --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> * llama : disable MPI for now ggml-ci * train : make KQ_pos memory buffer permanent via dummy scale op * ggml : revert change to ggml_cpy, add ggml_cont_Nd instead (#3275) ggml-ci * parallel : fix bug (extra BOS) + smaller token_prev array * parallel : fix cases where the input prompts can overflow the batch * parallel : add disabled experimental batch chunking in powers of two * llama : llama.h formatting + comments * simple : add README.md * llama : fix kv cache heuristic when context is less than 32 * parallel : fix crash when `-n -1` * llama : simplify returns if/else branches * metal : use mm kernels for batch size > 2 * examples : utilize new llama_get_logits_ith() * examples : add example for batched decoding * examples : do not eval prompt 2 times (close #3348) * server : clear the KV cache beyond n_past before llama_decode * server : avoid context swaps by shifting the KV cache --------- Co-authored-by: slaren <slarengh@gmail.com>	2023-09-28 19:04:36 +03:00