* host-swap tensor loop
the host-swap functionality is only triggered when the certain env. variables are declared
* target_include_directories tweak
* hot-swap tensor support
two intrusions:
1.) at the model loading to collect the snapshot
2.) the modification of the `/health` HTTP endpoint to be able to trigger the hot-swap via sending the `llama-server` the HTTP-request.
*both a braced by the specific env. variables
* hot-swap tensor support; graph invalidation
ggml_backend_cuda_invalidate_graphs export
* hot-swap tensor support
graph invalidation implementation; extended debug output (commented out)
* llama_reload_changed_tensors export
* tensor hot-swap on-demand reload
cpu-only/hybrid/gpu-only with split mode layer/graph full support implementation
* docs
* reuse the gguf parsing from llama.cpp
gguf_init_from_file, gguf_find_tensor, ggml_get_tensor
* remove the manual scheduling for hybrid inference
* update docs
* tensor shape validation
* update docs
* update docs
accidentally wiped the previous changes; so recovered them
* revert the GGML_CUDA_MAX_DEVICES to 16
* update llama_reload_changed_tensor
update llama_reload_changed_tensor, revert CMakeLists.txt
* update llama_reload_changed_tensor
* GGML_MAX_SRC
GGML_MAX_SRC compile-time definition support
* GGML_MAX_SRC
GGML_MAX_SRC compile-time definition support
* GGML_MAX_SRC
GGML_MAX_SRC compile-time definition support
* llama_reload_changed_tensor
update llama_reload_changed_tensor definition
* refactory
move the tensor-reloading implementation to llama-reload.cpp, llama-reload-info.h; some bugfixes and code reduction
* revert
added back the missing newline
* update docs
* reload_info constructor
* bugfix: cpu-only
TODO: improve the working environment by compiling for multiple hardware configurations; possibly make a test pipeline
* cpu-only bugfix
set the fix again after unsuccessful sync with main
* windows os compilation fix
#include <string>
* fix windows os build
error C2039: 'string': is not a member of 'std'
* remove dead file
* implement perplexity in server
* Revert "implement perplexity in server"
* gmp-oss: common
* gpt-oss: attnetion sinks, swiglu_oai
* gpt-oss: WIP llama
Model loads and runs (CPU only), but PPL is much to high
(~1500 for 1st batch vs ~200 in mainline).
Is it because of SWA, because of vocab, or did I introduce a bug somewhere?
* gpt-oss: CPU seems to be working
It was the SWA thta was missing in the previous commit.
There are issues with EOG tokens, so this still needs to be added.
* CUDA: ADD_ID
Just a copy from mainline
* gpt-oss: Seems to be working on CUDA
* gpt-oss: add sinks to the attn-vec kernels
* CUDA: add head size of 64 to new mma
Haven't turned it on yet, but observe slightly better PP and slightly
worse TG performance with that.
* gpt-oss: add ability to use -fmoe (only CUDA for now)
* Move row sums to the write place
* Add sinks to iqk flash attention
* gpt_oss: Implement -fmoe on the CPU
* Simdify swiglu_oai
Turning it off for now as performance becomes more variable,
so perhaps I'm running into thermal trottling imore often
because of making the CPU work too hard.
* llama: factor out model loader
* Builds successfully
* It runs, but mmap does not work
* Fix llama_mmap so mmap works
* Minor
* Fix CUDA after latest changes
* Attempt to use CUDA graphs with MoE models - not working
* CUDA graphs WIP - still not working
* CUDA graphs - seems to be working
Likely not all MLA variants are working.
I no longer remember why I added the q8_0 cpy that
transposes the tensor, but if really needed, this is now
missing. Also missing is q6_0.
* Make q8_0 cache work for DeepSeek models with CUDA graphs
* cuda: cpy for q6_0
* Fix llama_mmap on non-Linux platforms
* Adding forgotten file
* Iterating on Windows build failures
* cuda: re-add q8_0 -> q8_0 transpose
so mla = 2 can be used with CUDA graphs and q8_0 cache.
* Disable graphs without -fmoe
* Minor
* Turn graphs on by default
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Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
