Commit Graph

31 Commits

Author SHA1 Message Date
compilade
557410b8f0
llama : greatly reduce output buffer memory usage (#6122)
* llama : greatly reduce logits memory usage

* llama : more compact state saving and reloading

* llama : fix lctx.n_outputs not being set before building graph

* perplexity : adapt to the logits API changes

* perplexity : fix Winogrande, use correct logits for second choice start

The first logits used to evaluate the second choice were not from
the end of the common prefix; instead, they were the logits from the end
of the first choice. This has been corrected.

The previous implementation sometimes had outliers in the scores of
choices for some tasks, and the logic to skip choices words
in the log-likelihood evaluation probably was an attempt to reduce those,
but it was complex and didn't quite seem to be the right thing.

This is simpler now, and the outlier scores aren't there anymore.

* perplexity : normalize spaces and punctuation in Winogrande sentences

* llama : fix embedding conditions

* llama : fix llama_get_embeddings_ith when the resulting id is 0

* llama : fix wrong n_outputs in llama_set_inputs

A mismatch happened when using a smaller n_ubatch than n_batch and then using
llama_batch_get_one(). The decision of what n_outputs should be now almost
fully depends on how lctx.n_outputs is set in llama_decode_internal.
The conditions are simpler this way.

* llama : when saving the state, recalculate n_outputs

This ensures the correct number of outputs for the entire previous batch
is stored in the session file, even when n_ubatch is smaller than n_batch.

* llama : fix not-skipping outputs of non-causal models

* llama : fix running a batch with n_outputs == 0

It previously worked because lctx.inp_out_ids was not initialized,
so it pointed to some garbage address which was somehow still valid when I
ran my tests.

* llama : keep same graph topology even when n_outputs == 0

* ggml : saner ggml_can_repeat with empty tensors

*  ggml : future-proof ggml_is_empty by using GGML_MAX_DIMS - 1

* ggml : do not multi-thread ops returning empty tensors

* ggml : make ggml_is_empty public and work with views

* llama : use a vector for ctx->output_ids

* llama : rework reallocation logic for llama_output_reserve

Now comparing the actual size with the new total size of the output buffer
to allow more efficient enabling and disabling of the embeddings
and/or logits output in the future.

* ggml : skip empty tensors in all backends

* llama : fix llama_output_reserve nullptr deref when new_size is 0

* perplexity : make Winogrande work as it does on master

The problems with the Winogrande implementation will
need to be fixed in a separate PR to ease review.

* llama : clearer error messages for invalid logits or embeddings ids

* llama : assert all models that can have inp_out_ids

Since the graph topology is now constant, this presence check
can be done even when there are no outputs.

* llama : assert logits and embd buffers exist before writing to them

* llama : handle errors from llama_output_reserve at call sites

* perplexity : make hellaswag and multiple-choice outputs identical to master

Due to how the KV cache is updated, the logprobs for tokens in a batch
are very slightly affected by the other tokens present in the batch,
so to make hellaswag and multiple-choice return exactly the same results
as on master, the last token of each sequence needs to be evaluated
even though its output is not used at all.

This will probably be changed back in the future to make these benchmarks
a tiny bit faster.

* perplexity : fix division by zero when using less than 100 multiple-choice tasks

* llama : allow loading state saved with a different ctx size

When loading a session file, the context size is now only required to be
at least enough to load the KV cells contained in that session file,
instead of requiring to use exactly the same context size as when saving.

Doing this enables the use-case of extending or shrinking the context size
of a saved session.

This breaks existing session files because the meaning of kv_buf_size
is slightly changed (previously it was the size of the whole KV cache,
now it's only the size of the saved part of it). This allows for
finer-grained sanity checks when loading in an effort to keep kv_buf_size
useful even when the kv_size is changed.

* llama : minor

ggml-ci

* readme : update recent API changes, and warn about Vulkan

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-26 16:46:41 +02:00
Michael Podvitskiy
9fa2627347 ggml : introduce ggml_status (ggml/750)
* using enum as an exit code instead of macros

* update return type from enum to unsigned int

* indentation fix

* compound update
ggml_compute_exit_code -> ggml_status
changed ggml_status from a bit-field type to simple codes
ggml_status to string cast

* ggml_status to string cast

* GGML_CALL was removed

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

---------

Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-04 20:54:23 +02:00
Georgi Gerganov
ab336a9d5e
code : normalize enum names (#5697)
* coda : normalize enum names

ggml-ci

* code : cont

* code : cont
2024-02-25 12:09:09 +02:00
slaren
fbe7dfa53c
ggml : add max buffer sizes to opencl and metal backends (#5181) 2024-01-29 10:05:13 +02:00
0cc4m
2307523d32
ggml : add Vulkan backend (#2059)
* Vulkan loader code

* Fix matmul kernel, continue implementation

* Continue implementation

* Vulkan memory management

* Vulkan development

* Matmul call

* Add aligned malloc and free for VMA

* Continue implementation

* First matmul success

* GEMM Kernel optimization

* 1D Blocktiling

* 2D Blocktiling

* Write coalescing

* Continue vulkan implementation and optimization

* First FP16 attempt, disabled for now

* Code abstraction, FP16 implementation, fix kernel, add FP16 to FP32 kernel

* Enable device extensions properly, restore fp16 matmul op

* Fix mulmat_f16

* Output FP32 in fp16 matmul shader

* Fix f16_to_f32 kernel

* dequant_q4_0 kernel

* Add VMA library

* Avoid requesting dedicated memory, VMA can decide that by itself

* Add bounds checking to matmul kernels, improve implementation, fix command buffers not freed properly

* add cmake commands

* Add 2d write operation, profiling code

* Fix 2d write

* Fix queue selection for AMD RADV

* Fix trailing whitespace in vk_mem_alloc.h

* Add WIP warp tile mat mul shaders

* Disable glslc optimization

* Disable glslc optimization for CMake

* Optimize warptile matmul shader, replace blocktile with it

* Add split-k optimization for small matrix multiplication

Use semaphores for synchronization instead of fences or waitidle

Rework async write/read for synchronization

* Fix validation errors, improve compatibility with AMD GPUs

* Rework command buffer handling

* Variable matmul kernel using specialization constants

* Fix synchronization on AMD, add barriers for buffer ownership transfer, add debug flag and prints

* Reuse semaphores

* Handle stage flags during command buffer submission properly

* Increase matmul test runs for consistent results

* Fix F32 matmul

* Add vectorized loading and zeropadding for matrix multiplication

* Use pinned memory for f16 preprocessing

* Don't force aligned matmul

* Don't free before queue done

* Replace VMA library with native Vulkan buffer management

* Basic offloading support with mul_f32 and dmmv for q4_0

* Run glslc commands in parallel

* Unroll loops in dmmv shader

* Reduce usage of waitIdle

* Reuse pinned allocation for f16 conversion

* Handle devices with only a single queue

* Fix trailing whitespace in CMakeLists.txt

* Allow parallel execution of kernels, parallelize third and fourth dimension calls

* Add fallback for devices only supporting one DescriptorSet per DescriptorPool

* Move to graph function similar to CUDA implementation

* Use F16 kernel for most things, replace q_f32 with mul_mat_q_f16 function

* Add F32 dmmv shaders

* Batch submissions

* Add .spv to gitignore

* Split off matrix vector multiplication for separate optimization

* Use single command buffer for matrix vector multiplication ops

* Reduce overhead of mul_f32 calls by using a single command buffer

* Add submission batching to mul_f32

* Fix tests

* Add missing barrier

* Add further missing barrier

* Add further ops

* Replace vk::QueueFamilyIgnored with VK_QUEUE_FAMILY_IGNORED to support more Vulkan header versions

* Remove unnecessary cblas link

* Fix descriptor set pre-allocation assert

* Add runtime shader compilation, start transferring shaders to this approach

* Transfer remaining shaders to header and compile on runtime

* Fix fp32 fallback if device doesn't support fp16, add force disable env var GGML_VULKAN_DISABLE_F16

* Add support for q4_1, q5_0, q5_1 and q8_0

* Remove unnecessary scalar layout extension

* Parse graph early to pre-record command buffers

* Add q6_k support

* Add multi-submit for command buffers

* Fix q6_k dequant shader for AMD

* Fix q6_k for GPUs without fp16 support

* Simplify q6_k fp16 fix

* Minor fixes

* Fix wg_denom of m-mulmat shaders

* Add Python-based Vulkan shader generator

* Replace shaderc dependency with precompiled shaders

Fix python script to generate shaders

* Clean up code

* Fix shader generator script Windows compatibility

Co-authored-by: Concedo <39025047+LostRuins@users.noreply.github.com>

* Close file before deletion

* Fix vulkan shader fp32 name

* Add q2_k and q3_k support

Add validation check to compare shader results to cpu results

* Add q4_k support

* Add q5_k support

* Bake SPIR-V bytecode into the library instead of loading shaders from file

* Switch to signal semaphores for flexibility

Prepare broadcasting support for mul mat

* Finish broadcasting mul mat support for GQA

* Clean up unused functions

Add repeat op

* Add further ops, not yet enabled. Improve semaphore code

* Reduce number of used semaphores by utilizing timelines more properly

* Remove queue information

* Reuse timeline semaphores, allow parallel operation with binary semaphores to work around nvidia driver limitations

* Add Vulkan to llama-bench

* Remove cblas dependency

* Fix matmul k-split bug

* Fix q4_k dmmv K_QUANTS_PER_ITERATION 1 shader

* Add RMS Norm shader, rework op_f32 shader setup, fix matmul bug

* Fix issues with float16 overflows in shaders

* Fix issues with older Vulkan headers on Ubuntu 22.04

* Allow multi-op partial offloading by parsing the graph to preallocate enough between-op buffers

* Implement further ops, rework op_f32 calls, fix bugs

* Finish full offloading support, add last remaining ops, fix bugs, remove redundant code

* Upload generated file ggml-vulkan-shaders.hpp, remove redundant shaders

* Merge upstream changes, fix conflicts, adapt soft_max op

* Fix Python and shader header format

* Free model gpu buffers on exit

* Use single queue per device to simplify code

* Add matmul shader support for running multiple calculations in parallel

* Switch from semaphore-synchronized multiple command buffers per op to single command buffer for multiple ops, whole graph if possible

* Fix missing event cast

* Replace uint64_t(-1) with UINT64_MAX, rename function for clarity

* Fix warning about empty C function parameters

* Fix compiler warnings

* Properly implement Vulkan backend buffer handling

* Fix oversized host staging buffers

* Simplify barrier synchronization calls

* Fix gcc warnings

* Implement max_size for backend buffer types to limit the size of a single allocation

* Use min of maxMemoryAllocationSize and maxBufferSize for device max allocation size

* refactor multi buf

* Disable unsupported ops to fix tests

* Check for maintenance4 support before using it

* Handle devices with only a single queue

* Fix single queue logic

* propagate buffer usage in multi buffers

* Implement rope_neox op

* Cleanup header and other files

* Simplify gpu_extras by removing events and putting staging memcpys into contexts

* Move queue into context

Add not-yet-enabled async backend ops

* Simplify context use, optimize matmul shader for warp size 64 (AMD GCN), fix split_k matmul shader optimization

* Add get_max_size to SYCL backend.

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

* llama : fix trailing whitespace

---------

Co-authored-by: Henri Vasserman <henv@hot.ee>
Co-authored-by: Concedo <39025047+LostRuins@users.noreply.github.com>
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-01-28 19:03:59 +02:00
0cc4m
a1d6df129b
Add OpenCL add kernel (#5151)
* Add OpenCL add kernel

* Put add kernel into different string to stay within MSVC string length limit, disable float16 support due to bad results
2024-01-26 23:07:32 +01:00
slaren
e7e4df031b
llama : ggml-backend integration (#4766)
* llama : ggml-backend integration

* ggml-backend : add names to buffers

* fix unmap after loading

* batched-bench : add tensor_split param

* llama : check for null tensor_split

* ggml-backend : increase GGML_MAX_BACKENDS

* improve graph splitting, partial fix for --no-kv-offload

* cuda : add ggml-backend split buffer support

* cuda : do not create buffer types for devices that don't exist (fixes usage without CUDA devices available)

* ggml : fix null backend dereference (#4807)

* ggml : fix null backend dereference

* ggml : also check ggml_backend_is_cpu

* test-backend-ops : check buffer allocation failures

* llama : add cparam (split_mode) and command line argument (--split-mode, -sm) to configure the split mode (none, layer or row)

* ggml : fix mul_mat_id work size

* llama : rewrite session kv load/set without graphs

* minor

* llama : only initialize used backends, free backends on context free

* llama : abort ctx if cuda backend init fails

* llama : rewrite lora with ggml-backend and compute on CPU

ggml-ci

* llama : only map to a backend buffer the region of the file mapping containing the tensors used in the buffer

* opencl : add ggml-backend buffer type

* cuda : only use batched_cublas with batched mat muls (fixes fp16 tg perf)

* llama : on Metal, by default offload the full model

ggml-ci

* metal : page align the data ptr (#4854)

* Apply suggestions from code review

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

* cuda : fix split buffer free

* address review comments

* llama-bench : add split-mode parameter

* fix whitespace

* opencl : fix double initialization

* server : add --split-mode parameter

* use async copy and compute to improve multi-gpu performance

ggml-ci

* use async memcpys to copy the graph outputs to the CPU

* fix opencl

* use a host buffer for the cpu compute buffer for faster copies to the gpu

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2024-01-12 20:07:38 +01:00
Jared Van Bortel
15f5d96037
build : fix build info generation and cleanup Makefile (#3920)
* cmake : fix joining of REAL_GIT_DIR

* fix includes with help from include-what-you-use

* make : remove unneeded deps and add test-rope target

* fix C includes in C++ source files

* Revert "fix includes with help from include-what-you-use"

This reverts commit 635e9fadfd.
2023-12-01 00:23:08 +02:00
shibe2
465219b914 CLBlast: Add outer loops over src0 for broadcasting in mulmat
Reduce repeated dequantization of the same data.
2023-10-20 22:30:52 +04:00
shibe2
1117d06607
opencl : fix element-wise multiplication (#3656) 2023-10-18 15:09:22 +03:00
shibe2
40e5ce054f CLBlast: Fix temporary buffer size for f16 conversion (wsize)
Fix buffer overflow.
Reduce the size to fit just one 2D slice.
Assert sufficient size.
2023-10-17 21:02:30 +04:00
shibe2
1e0e873c37
CLBlast: Fix matrix-vector multiplication (#3544) 2023-10-12 21:59:47 +02:00
shibe2
e2583cbc29 CLBlast: Fix handling of on-device tensor data
Fix uploading tensor data to device, including 3D, 4D, and non-contiguous tensors.
Use correct offsets into data that is already in VRAM.
Correct handling of OpenCL events when multiple commands are queued.
2023-10-05 18:25:23 +04:00
shibe2
665018c749
CLBlast: Add broadcast support for matrix multiplication (#3402)
Broadcast src0 into src1 across dimensions 2 and 3 when needed.
This is required for models that use GQA.
2023-10-02 21:26:15 +02:00
shibe2
36b904e200
ggml-opencl.cpp: Make private functions static (#3300) 2023-09-21 14:10:26 -04:00
slaren
bd33e5ab92
ggml-opencl : store GPU buffer in ggml_tensor::extra (#2994) 2023-09-04 14:59:52 +02:00
Wentai Zhang
6460f758db
opencl : fix a bug in ggml_cl_pool_malloc() for ggml_cl_mul_mat_f32() (#2955)
Co-authored-by: Wentai Zhang <wentaizhang@tencent.com>
2023-09-03 11:46:44 +03:00
Howard Su
481f793acc
Fix opencl by wrap #if-else-endif with \n (#2086) 2023-07-07 05:34:18 +02:00
Govlzkoy
14a2cc71f6
[ggml] fix index for ne03 value in ggml_cl_mul_f32 (#2088) 2023-07-04 07:50:00 +08:00
LostRuins
96a712ca1b
Porting the improved K-Quant CUDA kernels to OpenCL (#1966)
* Added broken new q4k quant

* xx + ib0

* Fix q2_k fast kernel

* Use preprocessor for QK_K

* Add q6_k fast matmul kernel

* ported q3k speedup successfully

* ported q2k and q5k speedups

* remove old dot kernels and template

* fixed global const struct types

* fixing address spaces

* fixed string too long CI issue

---------

Co-authored-by: 0cc4m <picard12@live.de>
2023-06-29 05:56:43 +02:00
Howard Su
3d59ec5935
ggml : fix warnings under MSVC (#1908) 2023-06-17 18:46:15 +03:00
0cc4m
d411968e99
opencl : support k-quants (#1836)
* Porting q2_k kernel to OpenCL

* Set global and local sizes for kernel calls for dequantizing k-quants

* Added q6_k kernel

* Fix q4_k opencl struct order

* Replace uchar with uint8_t

* Finish dequant kernels

* Added OpenCL DMMV kernels

* Fix q2_k, improve code

* Fix q3_k

* Shorten switch statements

* Improve code formatting

---------

Co-authored-by: Concedo <39025047+LostRuins@users.noreply.github.com>
2023-06-16 21:59:49 +03:00
Howard Su
58970a4c39
Leverage mmap for offloading tensors to GPU (#1597)
* Rebase to latest

* Show progress

* Add assert to make sure we only allocate temp buffer for non-CPU backend tensor

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

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2023-06-12 14:44:16 +02:00
Robert Sung-wook Shin
98ed165574
OpenCL: Add release memory (#1741)
* Add opencl release memory

* Rename function name
2023-06-09 18:24:40 +02:00
Johannes Gäßler
17366df842
Multi GPU support, CUDA refactor, CUDA scratch buffer (#1703)
* CUDA multi GPU + scratch

ggml_cuda_compute_forward

Tensor parallelism

ggml_cuda_add

ggml_cuda_rms_norm

ggml_cuda_silu

CUDA scratch buffer

--main-gpu CLI option
2023-06-06 21:33:23 +02:00
LostRuins
d5b111f53d
Clblast fixes + enhancements to save VRAM and offload more layers (#1675)
* Use events instead of clFinish, where possible

* OpenCL: Don't load gpu layers into RAM, add mul_f32 kernel

* Reduce queueing overhead for contiguous tensors by using single mul kernel call

* Adapt to #1612 cl_mem malloc changes

* Reduce code duplication between cuda and opencl branches

* Improve implementation

* Clblast fixes + enhancements to save VRAM:

1. Change all Clblast buffers to CL_MEM_READ_WRITE, as the pool malloc currently doesn't properly handle them.
2. When recycling buffers in pool malloc, always assign the SMALLEST available buffer that fits, instead of the FIRST available buffer
3. When failing to recycle a buffer in pool malloc (all too small), instead recycle the largest available free buffer by resizing it.

* change max value size_t to use limits

* removed flags from the CL pool malloc, apply code tidying suggestions.
2023-06-06 19:00:01 +02:00
0cc4m
dcb2ed4826
OpenCL: Fix duplication of layers in VRAM and RAM, add GPU mul kernel (#1653)
* Use events instead of clFinish, where possible

* OpenCL: Don't load gpu layers into RAM, add mul_f32 kernel

* Reduce queueing overhead for contiguous tensors by using single mul kernel call

* Adapt to #1612 cl_mem malloc changes

* Reduce code duplication between cuda and opencl branches

* Improve implementation
2023-06-04 08:12:05 +02:00
Howard Su
bb051d9723
opencl : no need to allocate cl_mem on heap (#1612) 2023-05-28 20:13:36 +03:00
Howard Su
ca74884f66
opencl : use strstr to check if fp16 supported (#1611)
* Use strstr to check if fp16 supported

* Ensure ext_buffer is null terminated
2023-05-28 20:09:56 +03:00
Maarten ter Huurne
7d873811f3
Fix handling of "invalid property" when creating OpenCL command queue (#1565)
The `clCreateCommandQueue()` function will return the code
`CL_INVALID_QUEUE_PROPERTIES` when passed unsupported properties,
not `CL_INVALID_PROPERTY` as the original code was checking for.
2023-05-23 19:01:15 +03:00
0cc4m
2e6cd4b025
OpenCL Token Generation Acceleration (#1459)
* Move back to C++ for OpenCL

* Refactor OpenCL code to work more like the CUDA code, add missing functions

* Deduplicate dequant kernels

* Add OpenCL compile options

* Use compile args for preprocessing constants

* Restore default platform + device selection by id behavior

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
Co-authored-by: Henri Vasserman <henv@hot.ee>
2023-05-23 00:33:24 +03:00