Commit graph

433 commits

Author SHA1 Message Date
Georgi Gerganov 8a0f8673ba
ggml : export symbols (#1155) 2023-04-24 22:18:25 +03:00
xaedes 0c5692345d
examples : add save_load_state example (#1150)
* add save_load_state example

* use <cstdio> instead of <iostream> and fprintf / printf instead of cout

* renamed save-load-state example files replacing underscores by dashes
2023-04-24 19:23:31 +03:00
Georgi Gerganov 957c8ae21d
llama : increase scratch buffer size for 65B (ref #1152)
Temporary solution
2023-04-24 18:47:30 +03:00
mgroeber9110 9b0a4d4214
examples/main README improvements and some light refactoring (#1131) 2023-04-24 15:45:32 +00:00
Stephan Walter 2ec83428de
Fix build for gcc 8 and test in CI (#1154) 2023-04-24 15:38:26 +00:00
slaren e4cf982e0d
Fix cuda compilation (#1128)
* Fix: Issue with CUBLAS compilation error due to missing -fPIC flag

---------

Co-authored-by: B1gM8c <89020353+B1gM8c@users.noreply.github.com>
2023-04-24 17:29:58 +02:00
Georgi Gerganov c4fe84fb0d
llama : refactor get / set state + remove redundant kv cache API (#1143) 2023-04-24 07:40:02 +03:00
slaren 1d78fecdab
Fix LoRA acronym (#1145) 2023-04-23 23:03:44 +02:00
Georgi Gerganov 284685f169
scripts : add helper scripts to synch ggml repo 2023-04-23 19:57:09 +03:00
DannyDaemonic edce63baa9
Added README.md for main with examples and explanations (#1139) 2023-04-23 15:37:02 +00:00
Georgi Gerganov ec9cdb6752
ggml : do not print perf ops that have not been used at all 2023-04-23 18:32:52 +03:00
Georgi Gerganov e4422e299c
ggml : better PERF prints + support "LLAMA_PERF=1 make" 2023-04-23 18:15:39 +03:00
Stephan Walter 53c8434398
Improve AVX2 for vec_dot_q4_3_q8_0 (#1138) 2023-04-23 11:01:03 +00:00
Pavol Rusnak c6524f46eb
readme : update gpt4all instructions (#980) 2023-04-23 10:21:26 +02:00
Yishuo Wang c9e2c26f41
A better packNibbles and mul_sum_i8_pairs_float implementation using AVX512 (#1119) 2023-04-23 07:57:05 +00:00
Georgi Gerganov 0e018fe008
ggml : fix Q4_3 cuBLAS 2023-04-22 16:32:07 +03:00
Stephan Walter 857308d1e8
ci : trigger CI for drafts, but not most PR actions (#1125) 2023-04-22 16:12:29 +03:00
Stephan Walter c50b628810
Fix CI: ARM NEON, quantization unit tests, editorconfig (#1122) 2023-04-22 10:54:13 +00:00
unbounded 5f939498d5
ggml : unit test for quantization functions (#953)
* Unit test for quantization functions

Use the ggml_internal_get_quantize_fn function to loop through all
quantization formats and run a sanity check on the result.

Also add a microbenchmark that times these functions directly without
running the rest of the GGML graph.

* test-quantize-fns: CI fixes

Fix issues uncovered in CI
 - need to use sizes divisible by 32*8 for loop unrolling
 - use intrinsic header that should work on Mac

* test-quantize: remove

Per PR comment, subsumed by test-quantize-fns

* test-quantize: fix for q8_0 intermediates
2023-04-22 12:10:39 +03:00
wbpxre150 36b4f7e064
llama : print timings on ctrl+c exit (#1021)
* print timings on ctrl+c exit

* remove redundant free memory call.

* add global pointer to ctx.
2023-04-22 11:56:35 +03:00
eiery 10f19c1121
llama : have n_batch default to 512 (#1091)
* set default n_batch to 512 when using BLAS

* spacing

* alternate implementation of setting different n_batch for BLAS

* set n_batch to 512 for all cases
2023-04-22 11:27:05 +03:00
Howard Su 7e312f165c
cmake : fix build under Windows when enable BUILD_SHARED_LIBS (#1100)
* Fix build under Windows when enable BUILD_SHARED_LIBS

* Make AVX512 test on Windows to build the shared libs
2023-04-22 11:18:20 +03:00
Georgi Gerganov 872c365a91 ggml : fix AVX build + update to new Q8_0 format 2023-04-22 11:08:12 +03:00
Georgi Gerganov 955ef9a5d5
ggml : alternative Q4_3 implementation using modified Q8_0 (#1109)
* ggml : prefer vzip to vuzp

This way we always use the same type of instruction across all quantizations

* ggml : alternative Q4_3 implementation using modified Q8_0

* ggml : fix Q4_3 scalar imlpementation

* ggml : slight improvement of Q4_3 - no need for loop unrolling

* ggml : fix AVX paths for Q8_0 quantization
2023-04-22 10:55:35 +03:00
Stephan Walter c5aa5e5777
ggml : AVX2 optimization for vec_dot_q4_3_q8_0 and refactoring (#1099)
* AVX2 optimization for vec_dot_q4_3_q8_0 and refactoring

* finish AVX vectorization of quantize_row_q8_0

* Rename hsum_int_8 to hsum_i32_8
2023-04-22 10:37:05 +03:00
Clint Herron e9a9cb0c54
examples : Improve Alpaca Default Repeat Penalty: Better Match Alpaca.cpp Experience (#1107)
* Moving parameters to separate lines for readability.

* Increasing repeate_penalty to 1.1 to make alpaca more usable by default.

* Adding trailing newline.
2023-04-22 09:54:33 +03:00
xaedes b6e7f9b09e
llama : add api for getting/setting the complete state: rng, logits, embedding and kv_cache (#1105)
* reserve correct size for logits

* add functions to get and set the whole llama state:

including rng, logits, embedding and kv_cache

* remove unused variables

* remove trailing whitespace

* fix comment
2023-04-22 09:21:32 +03:00
slaren 50cb666b8a
Improve cuBLAS performance by using a memory pool (#1094)
* Improve cuBLAS performance by using a memory pool

* Move cuda specific definitions to ggml-cuda.h/cu

* Add CXX flags to nvcc

* Change memory pool synchronization mechanism to a spin lock
General code cleanup
2023-04-21 21:59:17 +02:00
apaz 25d7abbd1f
llama : fixed rlimit error message (#888) 2023-04-21 21:48:06 +03:00
源文雨 018f2279f5
cmake : link threads publicly to ggml (#1042)
* fix: ld link test-tokenizer-0 error

```
cmake3 --build . --config Release
[  5%] Built target ggml
[ 16%] Built target llama
[ 22%] Linking CXX executable ../bin/test-tokenizer-0
../libllama.a(ggml.c.o):在函数‘ggml_graph_compute’中:
ggml.c:(.text+0xf2db):对‘pthread_create’未定义的引用
ggml.c:(.text+0xf9d4):对‘pthread_join’未定义的引用
collect2: error: ld returned 1 exit status
gmake[2]: *** [bin/test-tokenizer-0] 错误 1
gmake[1]: *** [tests/CMakeFiles/test-tokenizer-0.dir/all] 错误 2
gmake: *** [all] 错误 2
```

* Update CMakeLists.txt

* Update CMakeLists.txt

* Update CMakeLists.txt
2023-04-21 21:27:06 +03:00
Alex Klinkhamer 9411288271
main : evaluate tokens in batches after swapping context (#1014)
* examples : evaluate tokens in batches after swapping context

* Update examples/main/main.cpp

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-04-21 21:18:09 +03:00
xaedes 8687c1f258
llama : remember and restore kv cache data pointers (#1104)
because their value is stored in buf and overwritten by memcpy
2023-04-21 18:25:21 +03:00
Kawrakow 1bfc153e2f
ggml : a faster version for Q4_1 x Q8_0 dot products (#1083)
* A faster version for Q4_1 x Q8_0 dot products

The idea nehind being that Q8_0 quantized
values get used many times in the matrix multiplications
where they are involved. In the current implementations,
when we are evaluating the dot products, we need to compute
the sum of the quants in the Q8_0 vector, so the same
operation is repeated many times. Here we pre-compute
the sum during Q8_0 quantization, store it in the
now modified block_q8_0 struct, and then reuse this
result in the subsequent dot products.

In a synthetic benchmark (just compute a bunch of dot
products), this change speeds up the Q4_1 * Q8_0 dot
product by 80%, making the performance identical to
Q4_0 * Q8_0.

In practical application, I see a ~15% gain in speed for
token prediction on M2, and ~5% gain on Ryzen 7950X.
The speed gain in the prompt evaluation is much bigger
(around 50%).

I have only done the change for the scalar version,
ARM_NEON, and AVX2, so we still need an AVX implementation.

* Cleaning up

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2023-04-21 18:18:26 +03:00
slaren 3d59769c3b
Show perplexity ETA in hours and minutes (#1096) 2023-04-21 14:57:57 +02:00
Georgi Gerganov d40fded93e
llama : fix comment for "output.weight" tensor 2023-04-21 10:24:02 +03:00
Stephan Walter 2510c1831f
Add ggml-model-*.bin checksums for 7B, 13B, 30B, 65B (#1088)
* Add ggml-model-*.bin checksums for 7B, 13B, 30B
* Add ggml-model-*.bin checksums for 65B

---------

Co-authored-by: Pavol Rusnak <pavol@rusnak.io>
2023-04-20 23:56:44 +02:00
Georgi Gerganov 12b5900dbc
ggml : sync ggml (add GPT-NeoX RoPE implementation) 2023-04-20 23:32:59 +03:00
Georgi Gerganov 9ff334f3c9
ggml : fix bug in ggml_compute_forward_dup_f32() 2023-04-20 21:58:38 +03:00
slaren 2005469ea1
Add Q4_3 support to cuBLAS (#1086) 2023-04-20 20:49:53 +02:00
Georgi Gerganov 8a1756abdf
ggml : do not break cuBLAS build (Q4_3 is not yet implemented) 2023-04-20 21:43:50 +03:00
Georgi Gerganov 66aab46079
ggml : fix Q4_3 quantization
Broke it during conflict resolution in last PR
2023-04-20 20:44:05 +03:00
Kawrakow 38de86a711
llama : multi-threaded quantization (#1075)
* Multi-threading quantization.

Not much gain for simple quantizations, bit it will be important
for quantizations that require more CPU cycles.

* Multi-threading for quantize-stats

It now does the job in ~14 seconds on my Mac for
Q4_0, Q4_1 and Q4_2. Single-threaded it was taking
more than 2 minutes after adding the more elaborate
version of Q4_2.

* Reviewer comments

* Avoiding compiler confusion

After changing chunk_size to const int as suggested by
@ggerganov, clang and GCC starting to warn me that I don't
need to capture it in the lambda. So, I removed it from the
capture list. But that makes the MSVC build fail. So,
making it a constexpr to make every compiler happy.

* Still fighting with lambda captures in MSVC

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-04-20 20:42:27 +03:00
Georgi Gerganov e0305ead3a
ggml : add Q4_3 quantization (#1082) 2023-04-20 20:35:53 +03:00
Ivan Komarov 6a9661ea5a
ci : remove the LLAMA_ACCELERATE matrix dimension from Ubuntu builds in the CI (#1074)
[Accelerate](https://developer.apple.com/documentation/accelerate) is an Apple framework which can only be used on macOS, and the CMake build [ignores](https://github.com/ggerganov/llama.cpp/blob/master/CMakeLists.txt#L102) the `LLAMA_ACCELERATE` variable when run on non-Apple platforms. This implies setting `LLAMA_ACCELERATE` is a no-op on Ubuntu and can be removed.

This will reduce visual noise in CI check results (in addition to reducing the number of checks we have to run for every PR). Right now every sanitized build is duplicated twice for no good reason (e.g., we have `CI / ubuntu-latest-cmake-sanitizer (ADDRESS, Debug, ON)` and `CI / ubuntu-latest-cmake-sanitizer (ADDRESS, Debug, OFF)`).
2023-04-20 18:15:18 +03:00
源文雨 5addcb120c
fix: LLAMA_CUBLAS=1 undefined reference 'shm_open' (#1080) 2023-04-20 15:28:43 +02:00
Stephan Walter c8c2c52482
AVX2 optimization for vec_dot_q4_2_q8_0 (#1068) 2023-04-20 08:45:41 +02:00
slaren 02d6988121
Improve cuBLAS performance by dequantizing on the GPU (#1065) 2023-04-20 03:14:14 +02:00
CRD716 834695fe3a
Minor: Readme fixed grammar, spelling, and misc updates (#1071) 2023-04-19 19:52:14 +00:00
Kawrakow f7d05095b4
Q4_2 quantization with rmse-optimized scale and quants (#1062)
* Q4_2 quantization with rmse-optimized scale and quants

For quantize-stats we get
q4_2: rmse 0.00159301, maxerr 0.17480469, 95pct<0.0030, median<0.0012

For 7B perplexity with BLAS enabled we get 6.2038 after 655 chunks.

Quantization is slow (~90 seconds on my Mac for 7B) as not
multi-threaded as in PR #896.

* ggml : satisfy the sanitizer builds

Not sure why this makes them fail

* Better follow ggml conventions for function names

* Fixed type as per reviewer comment

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-04-19 20:20:14 +02:00
Georgi Gerganov 884e7d7a2b
ggml : use 8-bit precision for Q4_1 intermediate results (#1047)
* ggml : use 8-bit precision for Q4_1 intermediate results (ARM)

* ggml : optimize ggml_vec_dot_q4_1_q8_0() via vmalq_n_f32

56 ms/token with Q4_1 !

* ggml : AVX2 implementation of ggml_vec_dot_q4_1_q8_0 (#1051)

* gitignore : ignore ppl-*.txt files

---------

Co-authored-by: slaren <2141330+slaren@users.noreply.github.com>
2023-04-19 20:10:08 +03:00