Commit Graph

112 Commits

Author SHA1 Message Date
Georgi Gerganov
706ff4c2e0
cuda : try to fix main device write 2023-10-27 22:17:47 +03:00
Georgi Gerganov
1a0843c493
cuda : utilize tensor cores with multiple GPU devices 2023-10-27 17:07:23 +03:00
Georgi Gerganov
2f9ec7e271
cuda : improve text-generation and batched decoding performance (#3776)
* cuda : prints wip

* cuda : new cublas gemm branch for multi-batch quantized src0

* cuda : add F32 sgemm branch

* cuda : fine-tune >= VOLTA params + use MMQ only for small batches

* cuda : remove duplicated cuBLAS GEMM code

* cuda : add CUDA_USE_TENSOR_CORES and GGML_CUDA_FORCE_MMQ macros

* build : add compile option to force use of MMQ kernels
2023-10-27 17:01:23 +03:00
Georgi Gerganov
6961c4bd0b
batched-bench : print params at start 2023-10-25 10:26:27 +03:00
Georgi Gerganov
b2f7e04bd3
sync : ggml (conv ops + cuda MSVC fixes) (#3765)
ggml-ci
2023-10-24 21:51:20 +03:00
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
Jan Ploski
f5f9121de1
llm : add MPT support (#3417)
* CUDA: added support for ggml_clamp (see also: https://github.com/ggerganov/ggml/issues/545)

* mpt : added an implementation based (mostly) on falcon integration, modified with deltas from ggml/examples/mpt

* mpt : protect against "clip_qkv": null in mpt-7b

* mpt : quick fix to avoid "Strange model" warning when quantizing MPT models

* mpt : addendum to changeset:84e30e8 - leave parameter clamp_kqv out from metadata rather than use 0.0 to indicate "no clamping" (more compliant with the current GGUF spec?)

* mpt : standardized all tensor names to follow GGUF spec

* mpt : addendum to changeset:1be89c40 - use "req" parameter of GGUF_GET_KEY macro instead of duplicate code

* mpt : fixed comment s/gptneox/mpt/

* mpt : remove tabs, trailing whitespace

* mpt : removed ne01 + n_past == ne00 assertion from alibi (cuda/f32) and rope_shift from build_mpt

* mpt : updated convert-mpt-hf-to-gguf.py to reflect changes made to convert-gptneox-hf-to-gguf.py in pr:3252

* comment out n_past instead of marking it unused

* mpt : removed hardcoded +178 from convert script in favor of utilizing hparams["vocab_size"]

* mpt : remove unused tokenizer_json in convert script

* ggml : remove obsolete n_past assert in ggml_alibi

* llama : print clam_kqv and max_alibi_bias hparams

---------

Co-authored-by: Cebtenzzre <cebtenzzre@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-10-10 10:50:23 +03:00
Georgi Gerganov
db3abcc114
sync : ggml (ggml-backend) (#3548)
* sync : ggml (ggml-backend)

ggml-ci

* zig : add ggml-backend to the build
2023-10-08 20:19:14 +03:00
slaren
f5ef5cfb18
ggml-cuda : perform cublas mat mul of quantized types as f16 (#3412)
* ggml-cuda : perform cublas matrix multiplication of quantized types as fp16

* rename CC_TURING to CC_VOLTA

* disable fp16 mat mul completely with multi GPU
2023-09-30 18:12:57 +02:00
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
slaren
da0400344b
ggml-cuda : perform cublas fp16 matrix multiplication as fp16 (#3370)
* ggml-cuda : perform cublas fp16 matrix multiplication as fp16

* try to fix rocm build

* restrict fp16 mat mul to volta and up
2023-09-28 13:08:28 +03:00
Johannes Gäßler
ee66942d7e
CUDA: fix peer access logic (#3231) 2023-09-17 23:35:20 +02:00
Johannes Gäßler
111163e246
CUDA: enable peer access between devices (#2470) 2023-09-17 16:37:53 +02:00
Johannes Gäßler
578d8c8f5c
CUDA: fix scratch malloced on non-main device (#3220) 2023-09-17 14:16:22 +02:00
Vlad
5dbc2b3213
Enable build with CUDA 11.0 (make) (#3132)
* CUDA 11.0 fixes

* Cleaner CUDA/host flags separation

Also renamed GGML_ASSUME into GGML_CUDA_ASSUME
2023-09-16 16:55:43 +02:00
Johannes Gäßler
0a5eebb45d
CUDA: mul_mat_q RDNA2 tunings (#2910)
* CUDA: mul_mat_q RDNA2 tunings

* Update ggml-cuda.cu

Co-authored-by: Henri Vasserman <henv@hot.ee>

---------

Co-authored-by: Henri Vasserman <henv@hot.ee>
2023-09-13 11:20:24 +02:00
Johannes Gäßler
4f7cd6ba9c
CUDA: fix LoRAs (#3130) 2023-09-13 00:15:33 +02:00
Johannes Gäßler
89e89599fd
CUDA: fix mul_mat_q not used for output tensor (#3127) 2023-09-11 22:58:41 +02:00
Johannes Gäßler
d54a4027a6
CUDA: lower GPU latency + fix Windows performance (#3110) 2023-09-11 19:55:51 +02:00
Johannes Gäßler
8a4ca9af56
CUDA: add device number to error messages (#3112) 2023-09-11 13:00:24 +02:00
Georgi Gerganov
b3e9852e47
sync : ggml (CUDA GLM RoPE + POSIX) (#3082)
ggml-ci
2023-09-08 17:58:07 +03:00
Jiahao Li
35195689cd
2x faster (rms) norm cuda kernels (3.7% e2e improvement) (#2985)
* 2x faster (rms) norm cuda kernels

* Fix code style
2023-09-04 08:53:30 +02:00
Engininja2
f04d002844
cuda : vsubss4 for older versions of ROCm/clang (#2942) 2023-09-01 23:33:19 +02:00
Johannes Gäßler
92b1bbd2ec
CUDA: fix RoPE asserts, block sizes (#2833) 2023-08-28 14:23:55 +03:00
Georgi Gerganov
eaa13a48ff
falcon : fix CUDA inference by making K and Q contiguous (#2830)
* falcon : fix CUDA inference by making K and Q contiguous

ggml-ci

* cuda : add assert to guard from non-cont ropes
2023-08-27 16:40:48 +03:00
Kawrakow
a6d1189fdd
k_quants tuning for Falcon-7b (#2816)
* Make ggml-cuda.cu build with QK_K = 64

Using LLAMA_CUDA_FORCE_DMMV = ON and -nommq it runs and produces
a meaningful result.

* k_quants tuning for Falcon-7b

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2023-08-27 15:19:59 +03:00
Henri Vasserman
6bbc598a63
ROCm Port (#1087)
* use hipblas based on cublas
* Update Makefile for the Cuda kernels
* Expand arch list and make it overrideable
* Fix multi GPU on multiple amd architectures with rocblas_initialize() (#5)
* add hipBLAS to README
* new build arg LLAMA_CUDA_MMQ_Y
* fix half2 decomposition
* Add intrinsics polyfills for AMD
* AMD assembly optimized __dp4a
* Allow overriding CC_TURING
* use "ROCm" instead of "CUDA"
* ignore all build dirs
* Add Dockerfiles
* fix llama-bench
* fix -nommq help for non CUDA/HIP

---------

Co-authored-by: YellowRoseCx <80486540+YellowRoseCx@users.noreply.github.com>
Co-authored-by: ardfork <134447697+ardfork@users.noreply.github.com>
Co-authored-by: funnbot <22226942+funnbot@users.noreply.github.com>
Co-authored-by: Engininja2 <139037756+Engininja2@users.noreply.github.com>
Co-authored-by: Kerfuffle <44031344+KerfuffleV2@users.noreply.github.com>
Co-authored-by: jammm <2500920+jammm@users.noreply.github.com>
Co-authored-by: jdecourval <7315817+jdecourval@users.noreply.github.com>
2023-08-25 12:09:42 +03:00
Georgi Gerganov
3f460a2b72
cuda : add RoPE kernel for mode == 2 (NeoX) (#2760)
* cuda : add RoPE kernel for mode == 2 (NeoX)

* falcon : do not offload the embeddings layer
2023-08-25 11:55:59 +03:00
Georgi Gerganov
cf658adc83
llm : add Falcon support (#2717)
* llama : refactor GGUF constants into static maps

* llama : check if model architecture is known

* llama : refactor llama_model_load_internal()

* gguf : add KV constant maps

* llm : read arch-specific KVs

* convert : add dummy scores + types

* falcon : load tensor data (CPU only)

* llama : fix loading progress bar

* llama : add arch member to llama_model

* falcon : CPU inference working

* falcon : support non-40B models

* falcon : minor

* llama : minor updates

ggml-ci

* convert-falcon-hf-to-gguf.py : fix special token mapping

* llama.cpp : llama default UNK token = id 0

* llama.cpp : fix bpe tokenizer

* llama.cpp : fix the fix of bpe tokenizer

* ggml : pass eps to ggml_norm

* metal : implement RoPE (mode = 2) + avoid ggml_repeat

* ggml : ggml_repeat always creates new tensor

* falcon : copy-paste self-attention from LLaMA

* metal : print extra compute pipeline info

* falcon : minor changes (still chasing the Metal problem)

* llama.cpp : fix linefeed token

* metal : fix GELU kernel numerical stability by using precise::tanh

* metal : temporary workaround for the concurrency optimization bug

* falcon : add CUDA offloading (#2739)

* llama : better model naming and size reporting

* llama : prep new tokenizer support

* llama : advanced BPE tokenizer based on ggllm.cpp imlpementation

* llama : remove oboslete comment

ggml-ci

* common : remove obsolete BPE API + disable test-tokenizer-1

* llama : revert BPE special-case in llama_byte_to_token()

* cuda : add TODOs for RoPE NeoX implementation

* llama : default special tokens based on vocab type

* perplexity : add log for start of tokenization

---------

Co-authored-by: klosax <131523366+klosax@users.noreply.github.com>
Co-authored-by: slaren <slarengh@gmail.com>
2023-08-23 23:08:04 +03:00
Johannes Gäßler
c63bb1d16a
CUDA: use mul_mat_q kernels by default (#2683) 2023-08-22 22:47:05 +02:00
Jiahao Li
800c9635b4
Fix CUDA softmax by subtracting max value before exp (#2665) 2023-08-22 20:27:06 +02:00
slaren
1123f7fbdf
ggml-cuda : use graph allocator (#2684)
use a different function for no_alloc to avoid breaking backwards compat, fixes lora

remove 512 n_batch limit

fixed 2048 batch size

cleanup

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2023-08-22 15:25:19 +02:00
Georgi Gerganov
ef3f333d37
ggml : sync latest (SAM + SD operators, CUDA alibi) (#2709)
* ggml : sync latest (SAM + SD operators, CUDA alibi)

ggml-ci

* ggml : fix tabs
2023-08-22 14:22:08 +03:00
slaren
097e121e2f
llama : add benchmark example (#2626)
* llama : add benchmark example

* add to examples CMakeLists.txt

* fix msvc build

* add missing include

* add Bessel's correction to stdev calculation

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* improve markdown formatting

* add missing include

* print warning is NDEBUG is not defined

* remove n_prompt and n_gen from the matrix, use each value separately instead

* better checks for non-optimized builds

* llama.cpp : fix MEM_REQ_SCRATCH0 reusing the value of n_ctx of the first call

* fix json formatting

* add sql output

* add basic cpu and gpu info (linx/cuda only)

* markdown: also show values that differ from the default

* markdown: add build id

* cleanup

* improve formatting

* formatting

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2023-08-18 12:44:58 +02:00
Johannes Gäßler
1cd06fa25e
CUDA: launch_bounds, small q4_K, q5_K mmq refactor (#2596) 2023-08-14 10:41:22 +02:00
Johannes Gäßler
f64d44a9b9
CUDA: Fixed OpenLLaMA 3b mmq, reduced compile time (#2590) 2023-08-13 00:24:45 +02:00
Johannes Gäßler
25d43e0eb5
CUDA: tuned mul_mat_q kernels (#2546) 2023-08-09 09:42:34 +02:00
Johannes Gäßler
f514d1b306
CUDA: faster k-quant mul_mat_q kernels (#2525) 2023-08-05 18:20:44 +02:00
Cebtenzzre
4329d1acb0
CUDA: use min compute capability of GPUs actually used (#2506) 2023-08-04 17:35:22 +02:00
Cebtenzzre
02f9d96a86
CUDA: check if event is NULL before cudaStreamWaitEvent (#2505)
Fixes #2503
2023-08-04 17:34:32 +02:00
Johannes Gäßler
468ea24fb4
CUDA: faster non k-quant mul_mat_q kernels (#2483) 2023-08-02 18:04:04 +02:00
Johannes Gäßler
4f6b60c776
CUDA: Fix models with output size != 32000 (#2480) 2023-08-02 16:48:10 +02:00
Johannes Gäßler
0728c5a8b9
CUDA: mmq CLI option, fixed mmq build issues (#2453) 2023-07-31 15:44:35 +02:00
Johannes Gäßler
1215ed7d5c
CUDA: Implemented row flattening for non-glm RoPE (#2468) 2023-07-31 14:32:30 +02:00
Johannes Gäßler
2dbf518911
CUDA: fewer memory bank conflicts for mul_mat_q (#2458) 2023-07-31 13:18:51 +02:00
Johannes Gäßler
11f3ca06b8
CUDA: Quantized matrix matrix multiplication (#2160)
* mmq implementation for non k-quants

* q6_K

* q2_K

* q3_k

* q4_K

* vdr

* q5_K

* faster q8_1 loading

* loop unrolling

* add __restrict__

* q2_K sc_high

* GGML_CUDA_MMQ_Y

* Updated Makefile

* Update Makefile

* DMMV_F16 -> F16

* Updated README, CMakeLists

* Fix CMakeLists.txt

* Fix CMakeLists.txt

* Fix multi GPU out-of-bounds
2023-07-29 23:04:44 +02:00
Johannes Gäßler
9baf9ef304
CUDA: faster multi GPU synchronization (#2448) 2023-07-29 23:04:10 +02:00
Kawrakow
129d844c87
Fix Q4_K and Q5_K for QK_K = 64 on CUDA (#2359)
* Fix Q4_K and Q5_K for QK_K = 64

* Very slightly better Q5_K bit fiddling

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2023-07-25 13:48:04 +03:00
slaren
41c674161f
make rms_norm_eps a parameter (#2374)
* make rms_norm_eps a parameter

* add rms_norm_eps to command line

* fix baby llama, test-grad0

* use scientific notation for eps param in the help

ggml-ci
2023-07-24 17:57:12 +02:00