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2023-04-30build: add armv{6,7,8} support to cmake (#1251)Pavol Rusnak
- flags copied from Makefile - updated comments in both CMakeLists.txt and Makefile to match reality
2023-04-29build : fix reference to old llama_util.hGeorgi Gerganov
2023-04-28ggml : add CLBlast support (#1164)0cc4m
* Allow use of OpenCL GPU-based BLAS using ClBlast instead of OpenBLAS for context processing * Improve ClBlast implementation, avoid recreating buffers, remove redundant transfers * Finish merge of ClBlast support * Move CLBlast implementation to separate file Add buffer reuse code (adapted from slaren's cuda implementation) * Add q4_2 and q4_3 CLBlast support, improve code * Double CLBlast speed by disabling OpenBLAS thread workaround Co-authored-by: Concedo <39025047+LostRuins@users.noreply.github.com> Co-authored-by: slaren <2141330+slaren@users.noreply.github.com> * Fix device selection env variable names * Fix cast in opencl kernels * Add CLBlast to CMakeLists.txt * Replace buffer pool with static buffers a, b, qb, c Fix compile warnings * Fix typos, use GGML_TYPE defines, improve code * Improve btype dequant kernel selection code, add error if type is unsupported * Improve code quality * Move internal stuff out of header * Use internal enums instead of CLBlast enums * Remove leftover C++ includes and defines * Make event use easier to read Co-authored-by: Henri Vasserman <henv@hot.ee> * Use c compiler for opencl files * Simplify code, fix include * First check error, then release event * Make globals static, fix indentation * Rename dequant kernels file to conform with other file names * Fix import cl file name --------- Co-authored-by: Concedo <39025047+LostRuins@users.noreply.github.com> Co-authored-by: slaren <2141330+slaren@users.noreply.github.com> Co-authored-by: Henri Vasserman <henv@hot.ee> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-04-22ggml : fix Q4_3 cuBLASGeorgi Gerganov
2023-04-22cmake : fix build under Windows when enable BUILD_SHARED_LIBS (#1100)Howard Su
* Fix build under Windows when enable BUILD_SHARED_LIBS * Make AVX512 test on Windows to build the shared libs
2023-04-21cmake : link threads publicly to ggml (#1042)源文雨
* 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
2023-04-20Improve cuBLAS performance by dequantizing on the GPU (#1065)slaren
2023-04-19ggml : Q4 cleanup - remove 4-bit dot product code (#1061)Stephan Walter
* Q4 cleanup * Remove unused AVX512 Q4_0 code
2023-04-19Add NVIDIA cuBLAS support (#1044)slaren
2023-04-18Adding a simple program to measure speed of dot products (#1041)Kawrakow
On my Mac, the direct Q4_1 product is marginally slower (~69 vs ~55 us for Q4_0). The SIMD-ified ggml version is now almost 2X slower (~121 us). On a Ryzen 7950X CPU, the direct product for Q4_1 quantization is faster than the AVX2 implementation (~60 vs ~62 us). --------- Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
2023-04-17Speedup the AVX-512 implementation of ggml_vec_dot_q4_0() (#933)Ivan Komarov
2023-04-15cmake : add finding the OpenBLAS header file (#992)katsu560
2023-04-13llama : merge llama_internal.h into llama.hGeorgi Gerganov
Hide it behind an #ifdef
2023-04-13cmake : add explicit F16C option (x86) (#576)anzz1
Fixes building for x86 processors missing F16C featureset MSVC not included, as in MSVC F16C is implied with AVX2/AVX512
2023-04-10Rewrite loading code to try to satisfy everyone:comex
- Support all three formats (ggml, ggmf, ggjt). (However, I didn't include the hack needed to support GPT4All files without conversion. Those can still be used after converting them with convert.py from my other PR.) - Support both mmap and read (mmap is used by default, but can be disabled with `--no-mmap`, and is automatically disabled for pre-ggjt files or on platforms where mmap is not supported). - Support multi-file models like before, but automatically determine the number of parts rather than requiring `--n_parts`. - Improve validation and error checking. - Stop using the per-file type field (f16) entirely in favor of just relying on the per-tensor type/size fields. This has no immediate benefit, but makes it easier to experiment with different formats, and should make it easier to support the new GPTQ-for-LLaMa models in the future (I have some work in progress on that front). - Support VirtualLock on Windows (using the same `--mlock` option as on Unix). - Indicate loading progress when using mmap + mlock. (Which led me to the interesting observation that on my Linux machine, with a warm file cache, mlock actually takes some time, whereas mmap without mlock starts almost instantly...) - To help implement this, move mlock support from ggml to the loading code. - madvise/PrefetchVirtualMemory support (based on #740) - Switch from ifstream to the `fopen` family of functions to avoid unnecessary copying and, when mmap is enabled, allow reusing the same file descriptor for both metadata reads and mmap (whereas the existing implementation opens the file a second time to mmap). - Quantization now produces a single-file output even with multi-file inputs (not really a feature as much as 'it was easier this way'). Implementation notes: I tried to factor the code into more discrete pieces than before. Regarding code style: I tried to follow the code style, but I'm naughty and used a few advanced C++ features repeatedly: - Destructors to make it easier to ensure everything gets cleaned up. - Exceptions. I don't even usually use exceptions when writing C++, and I can remove them if desired... but here they make the loading code much more succinct while still properly handling a variety of errors, ranging from API calls failing to integer overflow and allocation failure. The exceptions are converted to error codes at the API boundary.) Co-authored-by: Pavol Rusnak <pavol@rusnak.io> (for the bit I copied from #740)
2023-04-08cmake should link openblas properly with -lopenblas like how it's done in ↵eiery
the makefile (#839)
2023-03-31Enable -std= for cmake builds, fix warnings (#598)Stephan Walter
2023-03-30cmake : properly invoke CTest (#629)Stephan Walter
2023-03-28tests : free llama context at the end of the testGeorgi Gerganov
2023-03-28all : be more strict about converting float to double (#458)Stephan Walter
* Be more strict about converting float to double * Test equivalence of round, SILU implementations Test module is commented out in CMakeLists.txt because the tests may take a long time, depending on how much the compiler optimizes. * Fix softmax in perplexity.cpp * all : prefer float over double where appropriate * perplexity : add <cmath> --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-03-25CMake / CI additions (#497)anzz1
* CMake: Add AVX512 option * CI: Add AVX/AVX512 builds (Windows) (AVX512 tests can only be run when the worker happens to support it, building works anyway) * CMake: Fix sanitizer linkage ( merged #468 ) * CI: Add sanitizer builds (Ubuntu) * CI: Fix release tagging (change @zendesk/action-create-release to @anzz1/action-create-release until upstream PR Added commitish as input zendesk/action-create-release#32 is merged)
2023-03-25Overhaul the examples structureGeorgi Gerganov
- main -> examples - utils -> examples (renamed to "common") - quantize -> examples - separate tools for "perplexity" and "embedding" Hope I didn't break something !
2023-03-23Generate library with CMake (#430)nusu-github
* Generate library with CMake BUILD_SHARED_LIBS to allow llama library to be generated. * Turn ON PIC when BUILD_SHARED_LIBS is ON
2023-03-22cmake: make llama an actual library (#392)Erik Scholz
2023-03-22Introduce C-style API (#370)Georgi Gerganov
* Major refactoring - introduce C-style API * Clean up * Add <cassert> * Add <iterator> * Add <algorithm> .... * Fix timing reporting and accumulation * Measure eval time only for single-token calls * Change llama_tokenize return meaning
2023-03-21Add tokenizer test + revert to C++11 (#355)Georgi Gerganov
* Add test-tokenizer-0 to do a few tokenizations - feel free to expand * Added option to convert-pth-to-ggml.py script to dump just the vocabulary * Added ./models/ggml-vocab.bin containing just LLaMA vocab data (used for tests) * Added utility to load vocabulary file from previous point (temporary implementation) * Avoid using std::string_view and drop back to C++11 (hope I didn't break something) * Rename gpt_vocab -> llama_vocab * All CMake binaries go into ./bin/ now
2023-03-21Adding missing features of CMakeLists.txt & Refactoring (#131)nusu-github
* Functionality addition CMakeLists.txt Refactoring: 1. Simplify more options that are negation of negation. LLAMA_NO_ACCELERATE -> LLAMA_ACCELERATE 2. Changed to an optional expression instead of forcing to enable AVX2 in MSVC. 3. Make CMAKE_CXX_STANDARD, which is different from Makefile, the same. 4. Use add_compile_options instead of adding options to CMAKE_C_FLAGS. 5. Make utils use target_link_libraries instead of directly referencing code. Added features: 1. Added some options. LLAMA_STATIC_LINK,LLAMA_NATIVE,LLAMA_LTO,LLAMA_GPROF,LLAMA_OPENBLAS * Fix Accelerate link in CMake * Windows build Fix * C++11 to C++17 * Reflects C/C++ standard individually * Change the version to 3.12 --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2023-03-17add ptread link to fix cmake build under linux (#114)mmyjona
* add ptread link to fix cmake build under linux * add cmake to linux and macos platform * separate make and cmake workflow --------- Co-authored-by: Sebastián A <sebastian.aedo29@gmail.com>
2023-03-13CMake build in Release by default (#75)Georgi Gerganov
2023-03-13Initial support for CMake (#75)Sebastián A