This revamps how we discover GPUs in the system by leveraging the Ollama
runner. This should eliminate inconsistency between our GPU discovery and the
runners capabilities at runtime, particularly for cases where we try to filter
out unsupported GPUs. Now the runner does that implicitly based on the actual
device list. In some cases free VRAM reporting can be unreliable which can
leaad to scheduling mistakes, so this also includes a patch to leverage more
reliable VRAM reporting libraries if available.
Automatic workarounds have been removed as only one GPU leveraged this, which
is now documented. This GPU will soon fall off the support matrix with the next
ROCm bump.
Additional cleanup of the scheduler and discovery packages can be done in the
future once we have switched on the new memory management code, and removed
support for the llama runner.
This revamps how we discover GPUs in the system by leveraging the Ollama
runner. This should eliminate inconsistency between our GPU discovery and the
runners capabilities at runtime, particularly for cases where we try to filter
out unsupported GPUs. Now the runner does that implicitly based on the actual
device list. In some cases free VRAM reporting can be unreliable which can
leaad to scheduling mistakes, so this also includes a patch to leverage more
reliable VRAM reporting libraries if available.
Automatic workarounds have been removed as only one GPU leveraged this, which
is now documented. This GPU will soon fall off the support matrix with the next
ROCm bump.
Additional cleanup of the scheduler and discovery packages can be done in the
future once we have switched on the new memory management code, and removed
support for the llama runner.
libcap is not directly related to Vulkan and should be added by its own PR. It adds additional library dependencies for building and also requires users to run setcap or run ollama as root, which is not ideal for easy use
We prefer the nvcuda library, which reports driver versions. When we
dropped cuda v11, we added a safety check for too-old drivers. What
we missed was the cudart fallback discovery logic didn't have driver
version wired up. This fixes cudart discovery to expose the driver
version as well so we no longer reject all GPUs if nvcuda didn't work.
* readme: add Ellama to list of community integrations (#9800)
* readme: add screenpipe to community integrations (#9786)
* Add support for ROCm gfx1151 (#9773)
* conditionally enable parallel pipelines
* sample: make mutations in transforms explicit (#9743)
* updated minP to use early exit making use of sorted tokens
* ml/backend/ggml: allocate memory with malloc when loading model (#9822)
* runner: remove cache prompt flag from ollama runner (#9826)
We do not need to bypass the prompt caching in the ollama runner yet, as
only embedding models needed to bypass the prompt caching. When embedding
models are implemented they can skip initializing this cache completely.
* ollamarunner: Check for minBatch of context space when shifting
Models can specify that a group of inputs need to be handled a single
batch. However, context shifting didn't respect this and could trigger
a break anyways. In this case, we should instead trigger a context
shift earlier so that it occurs before the grouped batch.
Note that there still some corner cases:
- A long prompt that exceeds the context window can get truncated
in the middle of an image. With the current models, this will
result in the model not recognizing the image at all, which is
pretty much the expected result with truncation.
- The context window is set less than the minimum batch size. The
only solution to this is to refuse to load the model with these
settings. However, this can never occur with current models and
default settings.
Since users are unlikely to run into these scenarios, fixing them is
left as a follow up.
* Applied latest patches from McBane87
See this for details: https://github.com/whyvl/ollama-vulkan/issues/7#issuecomment-2708820861
Signed-off-by: Vadim Grinco <vadim@grinco.eu>
* Add ability to enable flash attention on vulkan (#4)
* discover: add flash attention handling for vulkan
* envconfig: fix typo in config.go
As part of the process some code was refactored and I added a new field
FlashAttention to GpuInfo since the previous solution didn't allow for a
granular check via vulkan extensions. As a side effect, this now allows
for granular per-device FA support checking in other places
---------
Signed-off-by: Vadim Grinco <vadim@grinco.eu>
Co-authored-by: zeo <108888572+zeozeozeo@users.noreply.github.com>
Co-authored-by: Louis Beaumont <louis.beaumont@gmail.com>
Co-authored-by: Daniel Hiltgen <dhiltgen@users.noreply.github.com>
Co-authored-by: Michael Yang <mxyng@pm.me>
Co-authored-by: Parth Sareen <parth.sareen@ollama.com>
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
Co-authored-by: Bruce MacDonald <brucewmacdonald@gmail.com>
Co-authored-by: Jesse Gross <jesse@ollama.com>
Co-authored-by: Nikita <50599445+nasrally@users.noreply.github.com>
* add build to .dockerignore
* test: only build one arch
* add build to .gitignore
* fix ccache path
* filter amdgpu targets
* only filter if autodetecting
* Don't clobber gpu list for default runner
This ensures the GPU specific environment variables are set properly
* explicitly set CXX compiler for HIP
* Update build_windows.ps1
This isn't complete, but is close. Dependencies are missing, and it only builds the "default" preset.
* build: add ollama subdir
* add .git to .dockerignore
* docs: update development.md
* update build_darwin.sh
* remove unused scripts
* llm: add cwd and build/lib/ollama to library paths
* default DYLD_LIBRARY_PATH to LD_LIBRARY_PATH in runner on macOS
* add additional cmake output vars for msvc
* interim edits to make server detection logic work with dll directories like lib/ollama/cuda_v12
* remove unncessary filepath.Dir, cleanup
* add hardware-specific directory to path
* use absolute server path
* build: linux arm
* cmake install targets
* remove unused files
* ml: visit each library path once
* build: skip cpu variants on arm
* build: install cpu targets
* build: fix workflow
* shorter names
* fix rocblas install
* docs: clean up development.md
* consistent build dir removal in development.md
* silence -Wimplicit-function-declaration build warnings in ggml-cpu
* update readme
* update development readme
* llm: update library lookup logic now that there is one runner (#8587)
* tweak development.md
* update docs
* add windows cuda/rocm tests
---------
Co-authored-by: jmorganca <jmorganca@gmail.com>
Co-authored-by: Daniel Hiltgen <daniel@ollama.com>
* llama: wire up builtin runner
This adds a new entrypoint into the ollama CLI to run the cgo built runner.
On Mac arm64, this will have GPU support, but on all other platforms it will
be the lowest common denominator CPU build. After we fully transition
to the new Go runners more tech-debt can be removed and we can stop building
the "default" runner via make and rely on the builtin always.
* build: Make target improvements
Add a few new targets and help for building locally.
This also adjusts the runner lookup to favor local builds, then
runners relative to the executable, and finally payloads.
* Support customized CPU flags for runners
This implements a simplified custom CPU flags pattern for the runners.
When built without overrides, the runner name contains the vector flag
we check for (AVX) to ensure we don't try to run on unsupported systems
and crash. If the user builds a customized set, we omit the naming
scheme and don't check for compatibility. This avoids checking
requirements at runtime, so that logic has been removed as well. This
can be used to build GPU runners with no vector flags, or CPU/GPU
runners with additional flags (e.g. AVX512) enabled.
* Use relative paths
If the user checks out the repo in a path that contains spaces, make gets
really confused so use relative paths for everything in-repo to avoid breakage.
* Remove payloads from main binary
* install: clean up prior libraries
This removes support for v0.3.6 and older versions (before the tar bundle)
and ensures we clean up prior libraries before extracting the bundle(s).
Without this change, runners and dependent libraries could leak when we
update and lead to subtle runtime errors.
Inforithmics
Daniel Hiltgen
Daniel Hiltgen
Masato Nakasaka
Michael Yang
Vadim Grinco
pufferffish
tomaThomas
yeongbba
Bruce MacDonald