Commit Graph

15 Commits

Author SHA1 Message Date
Michael Yang
fa7776fd24 gpt-oss (#11672)
* bf16

* tests

* gpt-oss

* enable gptoss for engine

* rough estimate

* convert to mxfp4

* handle safetensors U8

* clamp glu/linear

* update tokenizer

* MXFP4 support

This implements the Open Compute Microscaling (MX) FP4 format
as a tensor type with backend implementations focusing
on mulmat and mulmatid on CPU, CUDA, and Metal.

* Unit tests for MXFP4 support

This exercises various operations and shapes on both CPU and GPU (if detected
on the system)

* cuda graph

* unit test adjustments

* cuda: optimize memory access

Read 4 bytes at a time (8 elements) when performing mul_mat_vec_mxfp4

* mac: fix crash on old macos versions

cblas_sgemm is only supported on v13.3 and up, however bf16 is
only supported on v14+ so we were falling back to ggml-blas and
crashing on bf16 tensors.  Checking for the function being null
seems to be the simplest way to condittionally avoid registering the
backend.

* server: Minimum context length for gptoss

This model requires a minimum context length of 8192 to function
effectively. Users can set higher values through all normal mechanisms
but lower values will be silently reset.

* ggml: Multiply by numParallel for gptoss sliding window

When computing the graph size estimate, the context size is already
multiplied by numParallel so estimates reflect that. However, since
sliding window models use a smaller, fixed context size, they need
to manually take numParallel into account.

* gpt-oss integration

includes harmony parser and thinking levels, etc.

* fix sync

* fix tests

* fix lint

---------

Co-authored-by: Daniel Hiltgen <daniel@ollama.com>
Co-authored-by: Jesse Gross <jesse@ollama.com>
Co-authored-by: Devon Rifkin <drifkin@drifkin.net>
2025-08-05 12:21:16 -07:00
Jesse Gross
35fda7b4af ggml: Report ordinal IDs for AMD GPUs on Windows
We don't get valid UUIDs for AMD GPUs on Windows, so the best option
is to use the ordinal IDs. This brings us in line with what we currently
do on the Ollama server - the only exception is AMD GPUs on Linux, which
falls back to using ordinal IDs. The GGML implementation has no fallback
but it doesn't appear to occur for any of the GPUs that we support.

It's also possible that there are collisions between ordinal IDs for
different libraries - however the only places where we use them are
AMD on Windows and Metal on Mac, which can never occur on the same
system.
2025-07-09 10:35:31 -07:00
Jeffrey Morgan
6baf1e31e2 Revert "Revert "ggml: Export GPU UUIDs" (#11115)" (#11117)
Reverts PR #11115. The original change was mistakingly reverted instead of #10822
2025-06-18 07:30:49 -07:00
Jeffrey Morgan
ed567ef43b Revert "ggml: Export GPU UUIDs" (#11115)
This reverts commit aaa7818000.
2025-06-18 05:45:00 -07:00
Jesse Gross
aaa7818000 ggml: Export GPU UUIDs
This enables matching up devices and information reported by the backend
with system management libraries such as nvml to get accurate free
memory reporting.
2025-05-29 14:01:26 -07:00
Jesse Gross
6db8a3771c ggml: Report graph memory for failed allocations
GGML has a function to report the allocated size of a backend buffer.
However, this returns 0 if we tried to allocate a buffer and it failed.
For memory management purposes, it's important to know how much we were
trying to allocate. This extends the API to report attempted sizes for
all buffers and whether it succeeeded.
2025-05-22 14:38:09 -07:00
Michael Yang
23125648b8 chore: update mllama to use ollama engine (#10637) 2025-05-13 17:36:02 -07:00
Jeffrey Morgan
0cefd46f23 llama: update to commit de4c07f93 (#10655) 2025-05-12 12:17:26 -07:00
Jeffrey Morgan
8dd12c873d llama: update to commit e1e8e099 (#10513) 2025-05-01 18:24:09 -07:00
Jeffrey Morgan
e9e5f61c45 llama: update to commit 2016f07b (#10352) 2025-04-24 17:26:02 -07:00
Jeffrey Morgan
943464ccb8 llama: update to commit 71e90e88 (#10192) 2025-04-16 15:14:01 -07:00
Michael Yang
9e4642e9b3 ollama debug tensor 2025-03-11 14:49:19 -07:00
Jeffrey Morgan
4289c74359 llama: fix kv loading on snowflake-arctic-embed models (#9536) 2025-03-07 09:25:34 -08:00
Jeffrey Morgan
d7d7e99662 llama: update llama.cpp vendor code to commit d7cfe1ff (#9356) 2025-02-26 20:34:44 -08:00
Michael Yang
dcfb7a105c next build (#8539)
* 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>
2025-01-29 15:03:38 -08:00