Commit Graph

209 Commits

Author SHA1 Message Date
Diego Devesa
c83ad6d01e
ggml-backend : add device and backend reg interfaces (#9707)
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2024-10-03 01:49:47 +02:00
Alberto Cabrera Pérez
f536f4c439
[SYCL] Initial cmake support of SYCL for AMD GPUs (#9658)
sycl: initial cmake support of SYCL for AMD GPUs
2024-10-02 13:57:18 +01:00
Radoslav Gerganov
00b7317e63
vulkan : do not use tensor->extra (#9407)
* vulkan : do not use tensor->extra

This patch allows using the Vulkan backend with the RPC backend as
tensor->extra is no longer used.

Ref: #8536

* Adapt GGML_VULKAN_CHECK_RESULTS to extra removal (#2)

---------

Co-authored-by: 0cc4m <picard12@live.de>
2024-10-02 13:49:16 +03:00
Johannes Gäßler
e98c1c188e
test: fix OPT_STEP_ADAMW for test-backend-ops (ggml/974) 2024-10-01 16:07:40 +03:00
Salvatore Mesoraca
cb00020504
vulkan : mul_mat: fix UB with small warps (ggml/952)
When the device's warp size is less than 16,
it is possible for loadstride_a (mul_mm.comp:114)
and loadstride_b (mul_mm.comp:115) to be set to 0.
Because they are calculated as: the workgroup size,
multiplied by LOAD_VEC_* (which can be 1) and divided by 16.
And the workgroup size is set to be the same as the
warp/subgroup size.

The loadstride_* variables are used as increments in the
loops that populate the buffers used for the multiplication.

When they are 0 they cause an infinite loop.
But infinite loops without side-effects are UB and the
values of loadstride_* are known at compile time.
So, the compiler quietly optimizes all the loops away.
As a consequence, the buffers are not populated and
the multiplication result is just a matrix with all elements
set to 0.

We prevent the UB by making sure that the workgroup size
will never be less than 16, even if our device has a
smaller warp size (e.g. 8).

Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com>
2024-10-01 16:07:39 +03:00
Borislav Stanimirov
6c5322481a
ggml : fix ggml_cast (ggml/973) 2024-10-01 16:07:39 +03:00
Johannes Gäßler
7254cdf7e8
ggml: fix gradient allocation logic (ggml/966)
* ggml: fix gradient allocation logic

* gradient allocation in ggml_build_backward_expand

* fixup

* fix test-backend-ops grad

* suggestions by slaren

* fix test1.c

* fix legacy opt API

* fix test-grad0

* remove keep arg
2024-10-01 16:07:38 +03:00
Georgi Gerganov
cad341d889
metal : reduce command encoding overhead (#9698)
* metal : reduce command encoding overhead

ggml-ci

* metal : add comments
2024-10-01 16:00:25 +03:00
Georgi Gerganov
c919d5db39
ggml : define missing HWCAP flags (#9684)
ggml-ci

Co-authored-by: Willy Tarreau <w@1wt.eu>
2024-09-29 21:18:23 +03:00
Johannes Gäßler
aaa4099925
CUDA: remove bad assert (ggml/972) 2024-09-29 21:15:37 +03:00
Jeff Bolz
641002fba8
vulkan : multithread pipeline creation (ggml/963) 2024-09-29 21:15:37 +03:00
Jeff Bolz
0de8b203f1
vulkan : fix build for GGML_VULKAN_RUN_TESTS, add TFLOPS to log (ggml/961) 2024-09-29 21:15:37 +03:00
Salvatore Mesoraca
544f409b4b
vulkan : argsort barriers must be under uniform control flow (ggml/951)
a return before a barrier (that happens only in some threads in
a workgroup) leads to UB.
While the old code actually works on some devices,
it fails on some others (i.e. "smaller" GPUs).

BTW, I think it would be better to set specialization constants
when the graph is built, in that way the local workgroup
could be sized appropriately.
But it would take a lot of work.

Signed-off-by: Salvatore Mesoraca <s.mesoraca16@gmail.com>
2024-09-29 21:15:37 +03:00
Georgi Gerganov
6084bfb261
ggml : fix GGML_MAX_N_THREADS + improve formatting (ggml/969) 2024-09-29 21:15:35 +03:00
Dan Johansson
6a0f779484
ggml : add run-time detection of neon, i8mm and sve (#9331)
* ggml: Added run-time detection of neon, i8mm and sve

Adds run-time detection of the Arm instructions set features
neon, i8mm and sve for Linux and Apple build targets.

* ggml: Extend feature detection to include non aarch64 Arm arch

* ggml: Move definition of ggml_arm_arch_features to the global data section
2024-09-28 15:06:16 +03:00
Markus Tavenrath
89f9944981
Enable use to the rebar feature to upload buffers to the device. (#9251) 2024-09-28 12:05:05 +02:00
R0CKSTAR
7691654c68
mtgpu: enable VMM (#9597)
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2024-09-26 03:27:40 +02:00
Charles Xu
1e43630218
ggml : remove assert for AArch64 GEMV and GEMM Q4 kernels (#9217)
* ggml : remove assert for AArch64 GEMV and GEMM Q4 kernels

* added fallback mechanism when the offline re-quantized model is not
optimized for the underlying target.

* fix for build errors

* remove prints from the low-level code

* Rebase to the latest upstream
2024-09-25 16:12:20 +03:00
Dou Xinpeng
904837e0cb
cann: fix crash when llama-bench is running on multiple cann devices (#9627) 2024-09-25 11:30:38 +08:00
Eric Zhang
70392f1f81
ggml : add AVX512DQ requirement for AVX512 builds (#9622) 2024-09-24 11:03:21 +03:00
Georgi Gerganov
c038931615
examples : adapt to ggml.h changes (ggml/0)
ggml-ci
2024-09-24 11:00:52 +03:00
Georgi Gerganov
cea1486ecf
log : add CONT level for continuing previous log entry (#9610) 2024-09-24 10:15:35 +03:00
Max Krasnyansky
c087b6f11d
threads: fix msvc build without openmp (#9615)
We're missing atomic_thread_fence() in MSVC builds when openmp is disabled.
2024-09-23 21:18:48 -07:00
Ivan
116efee0ee
cuda: add q8_0->f32 cpy operation (#9571)
llama: enable K-shift for quantized KV cache
It will fail on unsupported backends or quant types.
2024-09-24 02:14:24 +02:00
Max Krasnyansky
f0c7b5edf8
threads: improve ggml_barrier scaling with large number of threads (#9598)
Make sure n_barrier and n_barrier_passed do not share the cache line to avoid cache line bouncing.
This optimization shows performance improvements even for n_threads <= 8 cases.

Resurect TSAN (Thread Sanitizer) check so that we can avoid doing expensive read-modify-write
in the normal case and just use thread-fence as originally intended.

---
Here is the original description and suggestions from Willy Tarreau :

There's currently some false sharing between n_barrier and
n_barrier_passed that is amplified in ggml_barrier() by the fact that
all threads need to increment n_barrier when entering, while all
previous threads continue to read n_barrier_passed, waiting for the last
one to release them all. The side effect is that all these readers are
slowing down all new threads by making the cache line bounce back and
forth between readers and writers.

Just placing them in two distinct cache lines is sufficient to boost
the performance by 21% on a 80-core ARM server compared to the
no-openmp version, and by 3% compared to the openmp version.

Note that the variables could have been spread apart in the structure
as well, but it doesn't seem that the size of this threadpool struct is
critical so here we're simply aligning them.

Finally, the same issue was present when leaving the barrier since all
threads had to update the n_barrier_passed counter, though only one
would add a non-zero value. This alone is responsible for half of the
cost due to undesired serialization.

It might be possible that using a small array of n_barrier counters
could make things even faster on many-core systems, but it would likely
complicate the logic needed to detect the last thread.

Co-authored-by: Willy Tarreau <w@1wt.eu>
2024-09-23 11:42:43 -07:00
Srihari-mcw
1e7b9299c6
ggml : AVX512 gemm for Q4_0_8_8 (#9532)
* AVX512 version of ggml_gemm_q4_0_8x8_q8_0

* Remove zero vector parameter passing

* Rename functions and rearrange order of macros

* Edit commments

* style : minor adjustments

* Update x to start from 0

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-09-23 17:06:38 +03:00
Georgi Gerganov
bf9c1013ac
metal : use F32 prec for K*Q in vec FA (#9595)
ggml-ci
2024-09-23 11:27:47 +03:00
Akarshan Biswas
e62e9789cd
Revert "[SYCL] fallback mmvq (#9088)" (#9579)
This reverts commit 50addec9a5.
2024-09-23 11:28:06 +08:00
R0CKSTAR
c35e586ea5
musa: enable building fat binaries, enable unified memory, and disable Flash Attention on QY1 (MTT S80) (#9526)
* mtgpu: add mp_21 support

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* mtgpu: disable flash attention on qy1 (MTT S80); disable q3_k and mul_mat_batched_cublas

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* mtgpu: enable unified memory

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* mtgpu: map cublasOperation_t to mublasOperation_t (sync code to latest)

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

---------

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2024-09-22 16:55:49 +02:00
Molly Sophia
912c331d3d
Fix merge error in #9454 (#9589)
Signed-off-by: Molly Sophia <mollysophia379@gmail.com>
2024-09-22 15:26:50 +02:00
Johannes Gäßler
a5b57b08ce
CUDA: enable Gemma FA for HIP/Pascal (#9581) 2024-09-22 09:34:52 +02:00
Molly Sophia
2a63caaa69
RWKV v6: RWKV_WKV op CUDA implementation (#9454)
* ggml: CUDA unary op EXP

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

* ggml: rwkv_wkv op CUDA impl

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>

---------

Signed-off-by: Molly Sophia <mollysophia379@gmail.com>
2024-09-22 04:29:12 +02:00
slaren
d09770cae7
ggml-alloc : fix list of allocated tensors with GGML_ALLOCATOR_DEBUG (#9573) 2024-09-21 14:24:23 +02:00
agray3
41f477879f
Update CUDA graph on scale change plus clear nodes/params (#9550)
* Avoid using saved CUDA graph if scale changes and reset nodes/params on update

Fixes https://github.com/ggerganov/llama.cpp/issues/9451

* clear before resize
2024-09-21 02:41:07 +02:00
Georgi Gerganov
d13edb17ed ggml : fix builds (#0)
ggml-ci
2024-09-20 21:15:05 +03:00
Georgi Gerganov
27609c49b9 ggml : fix trailing whitespace (#0)
ggml-ci
2024-09-20 21:15:05 +03:00
Johannes Gäßler
424c5d00a9 ggml/examples: add backend support for numerical optimization (ggml/949)
* CUDA eval works

* stochastic gradient descent op

* Adam except decay

* CUDA CROSS_ENTROPY_LOSS_BACK

* CUDA mnist-fc training works

* backend CLI arg

* refactor gguf load

* remove sched from opt_step_adam

* implement l1 regularization (weight decay)

* extra call to add optimizer

* initialize gradients with ggml_graph_reset

* gradient accumulation

* increment iter per eval instead of epoch

* adjust backend interfaces

* fix ggml_graph_reset without backend

* fix ggml graph export/import

* fixup

* rename

* revert ggml_opt changes

* more general CUDA repeat_back

* update documentation, fix CNN

* validation split

* add clarifying comment

* optimize PyTorch training

* adjust buffer size, thread count

* fix 0.0f validation split

* Update examples/mnist/mnist-common.cpp

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

* fix gradient accumulation

* tensor flag for accumulators -> tensor hash set

* Update include/ggml.h

Co-authored-by: slaren <slarengh@gmail.com>

* Update tests/test-backend-ops.cpp

Co-authored-by: slaren <slarengh@gmail.com>

* Update tests/test-backend-ops.cpp

Co-authored-by: slaren <slarengh@gmail.com>

* fix test prints

* Update src/ggml-backend.c

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

* better CUDA support for noncontiguous out_prod

* add comment

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: slaren <slarengh@gmail.com>
2024-09-20 21:15:05 +03:00
Georgi Gerganov
a6809c6a2e examples : add null threadpool args where needed (ggml/0)
ggml-ci
2024-09-20 21:15:05 +03:00
Johannes Gäßler
5cb12f6839
CUDA: fix sum.cu compilation for CUDA < 11.7 (#9562) 2024-09-20 18:35:35 +02:00
slaren
64c6af3195
ggml : fix n_threads_cur initialization with one thread (#9538)
* ggml : fix n_threads_cur initialization with one thread

* Update ggml/src/ggml.c

---------

Co-authored-by: Max Krasnyansky <quic_maxk@quicinc.com>
2024-09-18 10:13:08 -07:00
Max Krasnyansky
0226613853
threadpool : skip polling for unused threads (#9461)
* threadpool: skip polling for unused threads

Currently all threads do N polling rounds even if only 1 thread is active (n_threads_cur == 1).
This commit adds a check to skip the polling for unused threads (ith >= n_threads_cur).

n_threads_cur is now an atomic_int to explicitly tell thread sanitizer that it is written
from one thread and read from other threads (not a race conditions).

* threadpool: further simplify and improve ggml_barrier

Avoid using strict memory order while polling, yet make sure that all threads go through
full memory barrier (memory fence) on ggml_barrier entrace and exit.

* threads: add simple barrier test

This test does lots of small, parallel matmul ops where the barriers in between dominate the overhead.

* threadpool: improve thread sync for new-graphs

Using the same tricks as ggml_barrier. All the polling is done with relaxed memory order
to keep it efficient, once the new graph is detected we do full fence using read-modify-write
with strict memory order.

* threadpool: improve abort handling

Do not use threadpool->ec (exit code) to decide whether to exit the compute loop.
threadpool->ec is not atomic which makes thread-sanitizer rightfully unhappy about it.

Instead introduce atomic threadpool->abort flag used for this. This is consistent with
how we handle threadpool->stop or pause.

While at it add an explicit atomic_load for n_threads_cur for consistency.

* test-barrier: release threadpool before releasing the context

fixes use-after-free detected by gcc thread-sanitizer on x86-64
for some reason llvm sanitizer is not detecting this issue.
2024-09-17 11:19:46 +03:00
slaren
23e0d70bac
ggml : move common CPU backend impl to new header (#9509) 2024-09-16 16:22:07 +02:00
Michael Podvitskiy
a6a3a5c531
ggml : link MATH_LIBRARY not by its full path (#9339) 2024-09-16 14:06:50 +03:00
Georgi Gerganov
19514d632e
cmake : do not hide GGML options + rename option (#9465)
* cmake : do not hide GGML options

ggml-ci

* build : rename flag GGML_CUDA_USE_GRAPHS -> GGML_CUDA_GRAPHS

for consistency

ggml-ci
2024-09-16 10:27:50 +03:00
Eve
5c3d0f1824
ggml : IQ4_NL sgemm + Q4_0 AVX optimization (#9422)
* squashed

readd my iq4_nl sgemm PR https://github.com/ggerganov/llama.cpp/pull/8049

have ggml_vec_dot_q4_0 do two blocks per loop for avx

try out f16c ggml_vec_dot_iq4_nl, but it's not really faster. as per https://github.com/ggerganov/llama.cpp/pull/8549 we can calculate several blocks at a time with no issue

* shuffle

* remove f16c iq4_nl as i cant make it faster than before
2024-09-16 09:48:24 +03:00
Georgi Gerganov
c4965a64f7
metal : handle zero-sized allocs (#9466) 2024-09-16 09:05:56 +03:00
Georgi Gerganov
6262d13e0b
common : reimplement logging (#9418)
https://github.com/ggerganov/llama.cpp/pull/9418
2024-09-15 20:46:12 +03:00
Michael Podvitskiy
6988da94a2
cmake : correct order of sycl flags (#9497) 2024-09-15 19:55:52 +03:00
Michael Podvitskiy
7596487beb
cmake : try to fix sycl+intel build (#9487) 2024-09-15 10:06:38 +03:00
Yuri Khrustalev
822b6322de
ggml : ggml_type_name return "NONE" for invalid values (#9458)
When running on Windows, the quantization utility attempts to print the types that are not set which leads to a crash.
2024-09-14 12:54:37 +03:00