Commit Graph

170 Commits

Author SHA1 Message Date
Georgi Gerganov
dba497e0c1
cmake : restore LLAMA_LLAMAFILE_DEFAULT 2024-04-25 21:37:27 +03:00
Georgi Gerganov
fa0b4ad252
cmake : remove obsolete ANDROID check 2024-04-25 18:59:51 +03:00
Justine Tunney
192090bae4
llamafile : improve sgemm.cpp (#6796)
* llamafile : improve sgemm.cpp

- Re-enable by default
- Fix issue described in #6716
- Make code more abstract, elegant, and maintainable
- Faster handling of weirdly shaped `m` an `n` edge cases

* Address review comments

* Help clang produce fma instructions

* Address review comments
2024-04-22 22:00:36 +03:00
Georgi Gerganov
3b8f1ec4b1
llamafile : tmp disable + build sgemm.o when needed (#6716)
* build : sgemm.o only when needed

ggml-ci

* llamafile : tmp disable due to MoE bug

ggml-ci
2024-04-17 23:58:26 +03:00
Georgi Gerganov
666867b799
ggml : fix llamafile sgemm wdata offsets (#6710)
ggml-ci
2024-04-16 23:50:22 +03:00
Justine Tunney
8cc91dc63c
ggml : add llamafile sgemm (#6414)
This change upstreams llamafile's cpu matrix multiplication kernels
which improve image and prompt evaluation speed. For starters, Q4_0
and Q8_0 weights should go ~40% faster on CPU. The biggest benefits
are with data types like f16 / f32, which process prompts 2x faster
thus making them faster than quantized data types for prompt evals.

This change also introduces bona fide AVX512 support since tinyBLAS
is able to exploit the larger register file. For example, on my CPU
llama.cpp llava-cli processes an image prompt at 305 tokens/second,
using the Q4_K and Q4_0 types, which has always been faster than if
we used f16 LLaVA weights, which at HEAD go 188 tokens/second. With
this change, f16 LLaVA performance leap frogs to 464 tokens/second.

On Intel Core i9-14900K this change improves F16 prompt perf by 5x.
For example, using llama.cpp at HEAD with Mistral 7b f16 to process
a 215 token prompt will go 13 tok/sec. This change has fixes making
it go 52 tok/sec. It's mostly thanks to my vectorized outer product
kernels but also because I added support for correctly counting the
number of cores on Alderlake, so the default thread count discounts
Intel's new efficiency cores. Only Linux right now can count cores.

This work was sponsored by Mozilla who's given permission to change
the license of this code from Apache 2.0 to MIT. To read more about
what's improved, and how it works, see: https://justine.lol/matmul/
2024-04-16 21:55:30 +03:00
Matt Clayton
8093987090
cmake : add explicit metal version options (#6370)
* cmake: add explicit metal version options

* Update CMakeLists.txt

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-29 09:27:42 +02:00
Jared Van Bortel
32c8486e1f
wpm : portable unicode tolower (#6305)
Also use C locale for ispunct/isspace, and split unicode-data.cpp from unicode.cpp.
2024-03-26 17:46:21 -04:00
Joseph Stahl
e190f1fca6
nix: make xcrun visible in Nix sandbox for precompiling Metal shaders (#6118)
* Symlink to /usr/bin/xcrun so that `xcrun` binary
is usable during build (used for compiling Metal shaders)

Fixes https://github.com/ggerganov/llama.cpp/issues/6117

* cmake - copy default.metallib to install directory

When metal files are compiled to default.metallib, Cmake needs to add this to the install directory so that it's visible to llama-cpp

Also, update package.nix to use absolute path for default.metallib (it's not finding the bundle)

* add `precompileMetalShaders` flag (defaults to false) to disable precompilation of metal shader

Precompilation requires Xcode to be installed and requires disable sandbox on nix-darwin
2024-03-25 17:51:46 -07:00
slaren
280345968d
cuda : rename build flag to LLAMA_CUDA (#6299) 2024-03-26 01:16:01 +01:00
slaren
ae1f211ce2
cuda : refactor into multiple files (#6269) 2024-03-25 13:50:23 +01:00
slaren
2f0e81e053
cuda : add LLAMA_CUDA_NO_PEER_COPY to workaround broken ROCm p2p copy (#6208)
* cuda : add LLAMA_CUDA_NO_PEER_COPY to workaround broken ROCm p2p copy

* add LLAMA_CUDA_NO_PEER_COPY to HIP build
2024-03-22 14:05:31 +01:00
Pierrick Hymbert
d01b3c4c32
common: llama_load_model_from_url using --model-url (#6098)
* common: llama_load_model_from_url with libcurl dependency

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-17 19:12:37 +01:00
Georgi Gerganov
381da2d9f0
metal : build metallib + fix embed path (#6015)
* metal : build metallib + fix embed path

ggml-ci

* metal : fix embed build + update library load logic

ggml-ci

* metal : fix embeded library build

ggml-ci

* ci : fix iOS builds to use embedded library
2024-03-14 11:55:23 +02:00
slaren
f30ea47a87
llama : add pipeline parallelism support (#6017)
* llama : add pipeline parallelism support for batch processing with multiple CUDA GPUs

ggml-ci

* server : add -ub, --ubatch-size parameter

* fix server embedding test

* llama : fix Mamba inference for pipeline parallelism

Tested to work correctly with both `main` and `parallel` examples.

* llama : limit max batch size to n_batch

* add LLAMA_SCHED_MAX_COPIES to configure the number of input copies for pipeline parallelism
default increase to 4 (from 2)

changing this value may improve performance for some systems, but increases memory usage

* fix hip build

* fix sycl build (disable cpy_tensor_async)

* fix hip build

* llama : limit n_batch and n_ubatch to n_ctx during context creation

* llama : fix norm backend

* batched-bench : sync after decode

* swiftui : sync after decode

* ggml : allow ggml_get_rows to use multiple threads if they are available

* check n_ubatch >= n_tokens with non-casual attention

* llama : do not limit n_batch to n_ctx with non-casual attn

* server : construct batch with size of llama_n_batch

* ggml_backend_cpu_graph_compute : fix return value when alloc fails

* llama : better n_batch and n_ubatch comment

* fix merge

* small fix

* reduce default n_batch to 2048

---------

Co-authored-by: Francis Couture-Harpin <git@compilade.net>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-03-13 18:54:21 +01:00
Georgi Gerganov
83796e62bc
llama : refactor unicode stuff (#5992)
* llama : refactor unicode stuff

ggml-ci

* unicode : names

* make : fix c++ compiler

* unicode : names

* unicode : straighten tables

* zig : fix build

* unicode : put nfd normalization behind API

ggml-ci

* swift : fix build

* unicode : add BOM

* unicode : add <cstdint>

ggml-ci

* unicode : pass as cpts as const ref
2024-03-11 17:47:47 +02:00
Gilad S
ecab1c75de
cmake : fix subdir for LLAMA_METAL_EMBED_LIBRARY (#5985) 2024-03-11 10:00:08 +02:00
AidanBeltonS
3814a07392
[SYCL] Add support for SYCL Nvidia target (#5738)
* Add support for nvidia target in CMake

* Update sycl read-me for Nvidia target

* Fix errors
2024-03-11 09:13:57 +08:00
Georgi Gerganov
8a3012a4ad
ggml : add ggml-common.h to deduplicate shared code (#5940)
* ggml : add ggml-common.h to shared code

ggml-ci

* scripts : update sync scripts

* sycl : reuse quantum tables

ggml-ci

* ggml : minor

* ggml : minor

* sycl : try to fix build
2024-03-09 12:47:57 +02:00
Radosław Gryta
1289408817
cmake : fix compilation for Android armeabi-v7a (#5702) 2024-02-25 12:53:11 +02:00
Haoxiang Fei
8dbbd75754
metal : add build system support for embedded metal library (#5604)
* add build support for embedded metal library

* Update Makefile

---------

Co-authored-by: Haoxiang Fei <feihaoxiang@idea.edu.cn>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-02-20 11:58:36 +02:00
Georgi Gerganov
d0e3ce51f4
ci : enable -Werror for CUDA builds (#5579)
* cmake : pass -Werror through -Xcompiler

ggml-ci

* make, cmake : enable CUDA errors on warnings

ggml-ci
2024-02-19 14:45:41 +02:00
Abhilash Majumder
13e2c771aa
cmake : remove obsolete sycl compile flags (#5581)
* rm unwanted sycl compile options

* fix bug

* fix bug

* format fix
2024-02-19 11:15:18 +02:00
Jared Van Bortel
a0c2dad9d4
build : pass all warning flags to nvcc via -Xcompiler (#5570)
* build : pass all warning flags to nvcc via -Xcompiler
* make : fix apparent mis-merge from #3952
* make : fix incorrect GF_CC_VER for CUDA host compiler
2024-02-18 16:21:52 -05:00
Georgi Gerganov
f3f28c5395
cmake : fix GGML_USE_SYCL typo (#5555) 2024-02-18 19:17:00 +02:00
Ananta Bastola
6e4e973b26
ci : add an option to fail on compile warning (#3952)
* feat(ci): add an option to fail on compile warning

* Update CMakeLists.txt

* minor : fix compile warnings

ggml-ci

* ggml : fix unreachable code warnings

ggml-ci

* ci : disable fatal warnings for windows, ios and tvos

* ggml : fix strncpy warning

* ci : disable fatal warnings for MPI build

* ci : add fatal warnings to ggml-ci

ggml-ci

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-02-17 23:03:14 +02:00
Georgi Gerganov
5bf2b94dd4
cmake : fix VULKAN and ROCm builds (#5525)
* cmake : fix VULKAN and ROCm builds

* cmake : fix (cont)

* vulkan : fix compile warnings

ggml-ci

* cmake : fix

ggml-ci

* cmake : minor

ggml-ci
2024-02-16 19:05:56 +02:00
Michael Podvitskiy
8084d55440
cmake : ARM intrinsics detection for MSVC (#5401) 2024-02-14 10:49:01 +02:00
Michael Podvitskiy
c4fbb6717c
CMAKE_OSX_ARCHITECTURES for MacOS cross compilation (#5393)
Co-authored-by: Jared Van Bortel <jared@nomic.ai>
2024-02-07 16:39:23 -05:00
Johannes Gäßler
098f6d737b
make: Use ccache for faster compilation (#5318)
* make: Use ccache for faster compilation
2024-02-05 19:33:00 +01:00
Welby Seely
277fad30c6
cmake : use set() for LLAMA_WIN_VER (#5298)
option() is specifically for booleans.

Fixes #5158
2024-02-03 23:18:51 -05:00
0cc4m
e920ed393d
Vulkan Intel Fixes, Optimizations and Debugging Flags (#5301)
* Fix Vulkan on Intel ARC

Optimize matmul for Intel ARC

Add Vulkan dequant test

* Add Vulkan debug and validate flags to Make and CMakeLists.txt

* Enable asynchronous transfers in Vulkan backend

* Fix flake8

* Disable Vulkan async backend functions for now

* Also add Vulkan run tests command to Makefile and CMakeLists.txt
2024-02-03 18:15:00 +01:00
Eve
1cfb5372cf
Fix broken Vulkan Cmake (properly) (#5230)
* build vulkan as object

* vulkan ci
2024-01-31 20:21:55 +01:00
Neo Zhang Jianyu
01684139c3
support SYCL backend windows build (#5208)
* support SYCL backend windows build

* add windows build in CI

* add for win build CI

* correct install oneMKL

* fix install issue

* fix ci

* fix install cmd

* fix install cmd

* fix install cmd

* fix install cmd

* fix install cmd

* fix win build

* fix win build

* fix win build

* restore other CI part

* restore as base

* rm no new line

* fix no new line issue, add -j

* fix grammer issue

* allow to trigger manually, fix format issue

* fix format

* add newline

* fix format

* fix format

* fix format issuse

---------

Co-authored-by: Abhilash Majumder <30946547+abhilash1910@users.noreply.github.com>
2024-01-31 08:08:07 +05:30
Jared Van Bortel
fbf1ddec69
Nomic Vulkan backend (#4456)
Signed-off-by: Jared Van Bortel <jared@nomic.ai>
Co-authored-by: niansa <anton-sa@web.de>
Co-authored-by: Adam Treat <treat.adam@gmail.com>
Co-authored-by: Aaron Miller <apage43@ninjawhale.com>
Co-authored-by: ToKiNoBug <tokinobug@163.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: slaren <slarengh@gmail.com>
2024-01-29 15:50:50 -05:00
Eve
172ac82629
cmake : fix Vulkan build (#5182) 2024-01-29 10:04:47 +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
Abhilash Majumder
0f648573dd
ggml : add unified SYCL backend for Intel GPUs (#2690)
* first update for migration

* update init_cublas

* add debug functio, commit all help code

* step 1

* step 2

* step3 add fp16, slower 31->28

* add GGML_LIST_DEVICE function

* step 5 format device and print

* step6, enhance error check, remove CUDA macro, enhance device id to fix none-zero id issue

* support main device is non-zero

* step7 add debug for code path, rm log

* step 8, rename all macro & func from cuda by sycl

* fix error of select non-zero device, format device list

* ren ggml-sycl.hpp -> ggml-sycl.h

* clear CMAKE to rm unused lib and options

* correct queue: rm dtct:get_queue

* add print tensor function to debug

* fix error: wrong result in 658746bb26702e50f2c59c0e4ada8e9da6010481

* summary dpct definition in one header file to replace folder:dpct

* refactor device log

* mv dpct definition from folder dpct to ggml-sycl.h

* update readme, refactor build script

* fix build with sycl

* set nthread=1 when sycl, increase performance

* add run script, comment debug code

* add ls-sycl-device tool

* add ls-sycl-device, rm unused files

* rm rear space

* dos2unix

* Update README_sycl.md

* fix return type

* remove sycl version from include path

* restore rm code to fix hang issue

* add syc and link for sycl readme

* rm original sycl code before refactor

* fix code err

* add know issue for pvc hang issue

* enable SYCL_F16 support

* align pr4766

* check for sycl blas, better performance

* cleanup 1

* remove extra endif

* add build&run script, clean CMakefile, update guide by review comments

* rename macro to intel hardware

* editor config format

* format fixes

* format fixes

* editor format fix

* Remove unused headers

* skip build sycl tool for other code path

* replace tab by space

* fix blas matmul function

* fix mac build

* restore hip dependency

* fix conflict

* ren as review comments

* mv internal function to .cpp file

* export funciton print_sycl_devices(), mv class dpct definition to source file

* update CI/action for sycl code, fix CI error of repeat/dup

* fix action ID format issue

* rm unused strategy

* enable llama_f16 in ci

* fix conflict

* fix build break on MacOS, due to CI of MacOS depend on external ggml, instead of internal ggml

* fix ci cases for unsupported data type

* revert unrelated changed in cuda cmake
remove useless nommq
fix typo of GGML_USE_CLBLAS_SYCL

* revert hip cmake changes

* fix indent

* add prefix in func name

* revert no mmq

* rm cpu blas duplicate

* fix no_new_line

* fix src1->type==F16 bug.

* pass batch offset for F16 src1

* fix batch error

* fix wrong code

* revert sycl checking in test-sampling

* pass void as arguments of ggml_backend_sycl_print_sycl_devices

* remove extra blank line in test-sampling

* revert setting n_threads in sycl

* implement std::isinf for icpx with fast math.

* Update ci/run.sh

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

* Update examples/sycl/run-llama2.sh

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

* Update examples/sycl/run-llama2.sh

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

* Update CMakeLists.txt

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

* Update CMakeLists.txt

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

* Update CMakeLists.txt

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

* Update CMakeLists.txt

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

* add copyright and MIT license declare

* update the cmd example

---------

Co-authored-by: jianyuzh <jianyu.zhang@intel.com>
Co-authored-by: luoyu-intel <yu.luo@intel.com>
Co-authored-by: Meng, Hengyu <hengyu.meng@intel.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-01-28 17:56:23 +02:00
Jared Van Bortel
bbe7c56c99
cmake : pass CPU architecture flags to nvcc (#5146) 2024-01-26 15:34:06 -05:00
Xuan Son Nguyen
2bed4aa3f3
devops : add intel oneapi dockerfile (#5068)
Co-authored-by: Xuan Son Nguyen <xuanson.nguyen@snowpack.eu>
2024-01-23 09:11:39 +02:00
XiaotaoChen
3ce7e8f8e7
llava : MobileVLM support (#4954)
* MobileVLM native implementation

* delete depthwise_conv_2d and permute_cpy relative code, replace the two by the existed functions, and opt ldp definition, support LLAMA_PERF option for CMake

* move android script to example/llava directory

* Fix the editor config checks

---------

Co-authored-by: Chenxiaotao03 <chenxiaotao03@meituan.com>
2024-01-22 15:09:35 +02:00
Herman Semenov
77bc1bbd05
cmake : add support for ccache (#5002)
* Added support ccache for speedup recompilation

* cmake : option to disable ccache

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2024-01-20 10:11:31 +02:00
Georgi Gerganov
9b6ea4263a
cmake : add ggml public headers (#5011) 2024-01-18 23:36:07 +02:00
ngc92
3e5ca7931c
pass cpu-architecture arguments only to host code (C;C++) (#4943) 2024-01-15 19:40:48 +01:00
Karthik Kumar Viswanathan
ac32902a87
llama : support WinXP build with MinGW 8.1.0 (#3419) 2024-01-14 10:41:44 +02:00
a-n-n-a-l-e-e
eec22a1c63
cmake : check for openblas64 (#4134)
openblas v0.3.22 64-bit pkg-config file is named openblas64.pc
https://github.com/OpenMathLib/OpenBLAS/issues/3790
2024-01-05 18:04:40 +02:00
Georgi Gerganov
91d38876df metal : switch back to default.metallib (ggml/681)
ggml-ci
2024-01-05 18:02:06 +02:00
Georgi Gerganov
58ba655af0
metal : enable shader debugging (cmake option) (#4705)
* ggml : disable fast-math for Metal (cmake build only)

ggml-ci

* metal : fix Metal API debug warnings

* cmake : add -fno-inline for Metal build (#4545)

* metal : fix API debug warnings

* metal : fix compile warnings

* metal : use uint64_t for strides

* cmake : rename option to LLAMA_METAL_SHADER_DEBUG

* metal : fix mat-vec Q8_0 kernel for BS > 1

* metal : normalize mat-vec kernel signatures

* cmake : respect LLAMA_QKK_64 option

* metal : fix mat-vec Q4_K kernel for QK_K == 64

ggml-ci
2024-01-02 10:57:44 +02:00
slaren
5bf3953d7e
cuda : improve cuda pool efficiency using virtual memory (#4606)
* cuda : improve cuda pool efficiency using virtual memory

* fix mixtral

* fix cmake build

* check for vmm support, disable for hip

ggml-ci

* fix hip build

* clarify granularity

* move all caps to g_device_caps

* refactor error checking

* add cuda_pool_alloc, refactor most pool allocations

ggml-ci

* fix hip build

* CUBLAS_TF32_TENSOR_OP_MATH is not a macro

* more hip crap

* llama : fix msvc warnings

* ggml : fix msvc warnings

* minor

* minor

* cuda : fallback to CPU on host buffer alloc fail

* Update ggml-cuda.cu

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

* Update ggml-cuda.cu

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

* ensure allocations are always aligned

* act_size -> actual_size

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2023-12-24 14:34:22 +01:00
Erik Garrison
0f630fbc92
cuda : ROCm AMD Unified Memory Architecture (UMA) handling (#4449)
* AMD ROCm: handle UMA memory VRAM expansions

This resolves #2797 by allowing ROCm AMD GPU users with a UMA to
dynamically expand the VRAM allocated to the GPU.

Without this, AMD ROCm users with shared CPU/GPU memory usually are
stuck with the BIOS-set (or fixed) framebuffer VRAM, making it
impossible to load more than 1-2 layers.

Note that the model is duplicated in RAM because it's loaded once for
the CPU and then copied into a second set of allocations that are
managed by the HIP UMA system. We can fix this later.

* clarify build process for ROCm on linux with cmake

* avoid using deprecated ROCm hipMallocHost

* keep simplifying the change required for UMA

* cmake: enable UMA-compatible allocation when LLAMA_HIP_UMA=ON
2023-12-21 21:45:32 +02:00