Commit Graph

112 Commits

Author SHA1 Message Date
Georgi Gerganov
593b344f2f ggml : do not print perf ops that have not been used at all 2023-04-23 18:32:52 +03:00
Georgi Gerganov
03a6e6f189 ggml : better PERF prints + support "LLAMA_PERF=1 make" 2023-04-23 18:15:39 +03:00
Stephan Walter
fe240a9faf Improve AVX2 for vec_dot_q4_3_q8_0 (#1138) 2023-04-23 11:01:03 +00:00
Yishuo Wang
6fde036756 A better packNibbles and mul_sum_i8_pairs_float implementation using AVX512 (#1119) 2023-04-23 07:57:05 +00:00
Georgi Gerganov
3ca1110186 ggml : fix Q4_3 cuBLAS 2023-04-22 16:32:07 +03:00
Stephan Walter
949ca5ce05 Fix CI: ARM NEON, quantization unit tests, editorconfig (#1122) 2023-04-22 10:54:13 +00:00
Georgi Gerganov
887673522d ggml : fix AVX build + update to new Q8_0 format 2023-04-22 11:08:12 +03:00
Georgi Gerganov
59fab3116a 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
9cecc39408 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
slaren
1e909c9209 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
Kawrakow
cae6483d88 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
Georgi Gerganov
9e824bf15c ggml : sync ggml (add GPT-NeoX RoPE implementation) 2023-04-20 23:32:59 +03:00
Georgi Gerganov
f04613a668 ggml : fix bug in ggml_compute_forward_dup_f32() 2023-04-20 21:58:38 +03:00
Georgi Gerganov
7a693926b8 ggml : do not break cuBLAS build (Q4_3 is not yet implemented) 2023-04-20 21:43:50 +03:00
Georgi Gerganov
c3aa2316ac ggml : fix Q4_3 quantization
Broke it during conflict resolution in last PR
2023-04-20 20:44:05 +03:00
Kawrakow
6e34a4c7c8 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
0a8cdb2ea1 ggml : add Q4_3 quantization (#1082) 2023-04-20 20:35:53 +03:00
Stephan Walter
091a53228c AVX2 optimization for vec_dot_q4_2_q8_0 (#1068) 2023-04-20 08:45:41 +02:00
slaren
881ecfb4ef Improve cuBLAS performance by dequantizing on the GPU (#1065) 2023-04-20 03:14:14 +02:00
Kawrakow
e0e10251a3 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
73a59affb2 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
Stephan Walter
ec0e355be1 ggml : Q4 cleanup - remove 4-bit dot product code (#1061)
* Q4 cleanup

* Remove unused AVX512 Q4_0 code
2023-04-19 19:06:37 +03:00
slaren
bc5977cc90 Add NVIDIA cuBLAS support (#1044) 2023-04-19 11:22:45 +02:00
slaren
dee44e099f Multi-threaded ggml_cpy (#1035)
* Multi-threaded ggml_cpy

* Update ggml.c

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* Also fix wdata offset in ggml_compute_forward_add_q_f32

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-04-19 00:53:24 +02:00
Georgi Gerganov
4207b4b129 ggml : add new Q4_2 quantization (ARM only) (#1046)
* ggml : Q4_2 ARM

* ggml : add ggml_is_quantized()

* llama : update llama_type_name() with Q4_2 entry

* ggml : speed-up q4_2

- 4 threads: ~100ms -> ~90ms
- 8 threads:  ~55ms -> ~50ms

* ggml : optimize q4_2 using vmlaq_n_f32 + vmulq_n_f32
2023-04-18 23:54:57 +03:00
Georgi Gerganov
5eaa6d25cf ggml : scratch that - vmlaq_n_f32 is always better
Had a background process that was messing with the timings
2023-04-18 23:11:23 +03:00
Georgi Gerganov
47aacf4239 ggml : optimize ggml_vec_dot_q4_0_q8_0() using vectorized accumulators 2023-04-18 22:59:17 +03:00
slaren
dc0fa95077 Add LoRA support (#820) 2023-04-17 17:28:55 +02:00
Georgi Gerganov
42ea22af13 ggml : avoid using ggml_fp16_to_fp32() and ggml_fp32_to_fp16() in ggml.c 2023-04-17 16:16:23 +03:00
Ivan Komarov
fb550a0f64 Speedup the AVX-512 implementation of ggml_vec_dot_q4_0() (#933) 2023-04-17 15:10:57 +02:00
Stephan Walter
0363b17de2 Fix potential int8 overflow in non-SIMD vec_dot (#986) 2023-04-15 18:28:56 +00:00
Stephan Walter
378ffbab0e Refactor ggml.c for future tensor types (#1001) 2023-04-15 16:25:38 +00:00
Georgi Gerganov
053915a751 ggml : add Q8_0 quantization for intermediate results (#951)
* ggml : add Q8_0 quantization for intermediate results

* quantize-stats : fix test + add it to Makefile default

* Q8: use int8_t, AVX/AVX2 optimizations

* ggml : fix quantize_row_q8_0() ARM_NEON rounding

* minor : updates after rebase to latest master

* quantize-stats : delete obsolete strings

* ggml : fix q4_1 dot func

---------

Co-authored-by: Stephan Walter <stephan@walter.name>
2023-04-15 17:53:22 +03:00
Georgi Gerganov
a15576393c ggml : use posix_memalign on non-Windows env 2023-04-15 14:25:45 +03:00
Pavol Rusnak
5de4cdb1fb Expose type name from ggml (#970)
Avoid duplication of type names in utils

Co-authored-by: Håkon H. Hitland <haakon@likedan.net>
2023-04-14 20:05:37 +02:00
Kerfuffle
0c6e3a6e6f ggml : add unary and binary map operations (#874)
* GGML map ops proof of concept.

* Various cleanups.

Add handling for task setting.

Add handling for ggml_compute_backward.

Rename functions to ggml_map_unary_f32 and ggml_map_binary_f32

Fix compiler warnings related to casting function pointers and `void *`

Reorder functions and definitions based on the GGML op number.

Use typedefs for map op function pointer types.

* Fix position of map ops cases in ggml_compute_forward
2023-04-14 17:43:55 +03:00
Georgi Gerganov
64179095f2 ggml : minor 2023-04-14 13:31:29 +03:00
Georgi Gerganov
ebc6e99a4a ggml : always allocate buffers with size multiple of GGML_MEM_ALIGN 2023-04-14 13:31:15 +03:00
Georgi Gerganov
d7f330d1c4 ggml : fix q4_1 dot product types 2023-04-14 09:45:42 +03:00
Howard Su
e0dbf8218f ggml : optimize rope function to avoid call powf in the tight loop (#807) 2023-04-14 09:24:52 +03:00
Georgi Gerganov
faf1c350cb ggml : add GGML_DEFAULT_N_THREADS 2023-04-13 18:36:48 +03:00
Georgi Gerganov
609adf4f48 ggml : speed-up ggml_vec_dot_q4_1() ARM_NEON + 32-bit ARM support (#900)
* ggml : speed-up q4_1 ARM_NEON by ~5%

* ggml : implement vaddvq when missing

* ggml : implement vminvq and vmaxvq when missing

* ggml : implement vzip when missing

* ggml : fix comment

* ggml : try to use correct ifdef
2023-04-13 18:32:36 +03:00
Stephan Walter
2bf3e1346e ggml : optimize non-SIMD Q4_0 vector dot product (#703) 2023-04-13 17:59:50 +03:00
Pavol Rusnak
3a62b13f43 ggml : introduce GGML_ALIGNED_MALLOC/GGML_ALIGNED_FREE macros (#884)
which allows us to use aligned_alloc or _aligned_malloc functions
2023-04-13 17:08:32 +03:00
Vladimir
bcc5569f59 ggml : update cblas_sgemm columns var to be more reasonable (#838) 2023-04-13 16:24:30 +03:00
Pavol Rusnak
e4d3b4b251 Fix whitespace, add .editorconfig, add GitHub workflow (#883) 2023-04-11 19:45:44 +00:00
Stephan Walter
c8296315db Add enum llama_ftype, sync ggml_type to model files (#709) 2023-04-11 15:03:51 +00:00
comex
74ad81e8a0 Windows fixes (#890)
Mostly for msys2 and mingw64 builds, which are different from each other
and different from standard Visual Studio builds.  Isn't Windows fun?

- Define _GNU_SOURCE in more files (it's already used in ggml.c for
  Linux's sake).

- Don't use PrefetchVirtualMemory if not building for Windows 8 or later
  (mingw64 doesn't by default).  But warn the user about this situation
  since it's probably not intended.

- Check for NOMINMAX already being defined, which it is on mingw64.

- Actually use the `increment` variable (bug in my `pizza` PR).

- Suppress unused variable warnings in the fake pthread_create and
  pthread_join implementations for Windows.

- (not Windows-related) Remove mention of `asprintf` from comment;
  `asprintf` is no longer used.

Fixes #871.
2023-04-11 15:19:54 +02:00
Georgi Gerganov
9c28c0bbd9 ggml : fix WASM build 2023-04-10 23:20:01 +03:00
Georgi Gerganov
2dbbb0ab85 ggml : add ggml_cont() + optimize ggml_cpy() for contiguous dst 2023-04-10 22:42:28 +03:00