* WIP: absorb adding input into std_attn and std_ffn
* WIP: NCCL infra
* WIP: add reduce and fake_cpy ops
* WIP
* WIP: graph appears to work, layer is broken
* WIP: Qwen3-MoE works with graph, layer still broken
* WIP: GLM-4.5 graph works
* WIP: fix sm layer (dense)
* WIP: fix sm layer (MoE)
* WIP: fast PP with bespoke 4-GPU NCCL
I guess, I'm not using NCCL the right way as PP is very
low with a single communicator group for 3 or more GPUs.
But if I create 4 communicator groups for pairs of GPUs
(0,1, 2,3, 0,2, 1,3) and use that, PP is fast: I'm hitting
1500 t/s for L3-70B on the 4x3090 system, which is
~20% better than the previous sm graph without NCCL.
But that cannot be the solution (I cannot be creating pairwise
communicators and associated logic for every possible number of GPUs).
* WIP: Cohere2
* Explicitely set device
* Bespoke 3-GPU case
* WIP
* Do not repeat get_rows multiple times
* Fix 3 GPUs
* OK, let's leave it in
* Simple async
* This sync seems enough
* Only do async for 4 or more backends
With 2 GPUs (so, 3 backends) not using async is slightly faster
* Scheduler changes
* Use OpenMP if available
Surprisingly (at least to me), this is quite a bit faster than
std::thread and std::barrier. GLM-4.5-AIR with 4 GPUs is now
at 105 t/s at zero context!
* Do not use OpenMP if there are tensor overrides
* Set omp max active levels
* Be more careful with having set the device before using a stream
* Command line option to turn on async. Set to false by defualt for now
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
* Add RPC backend in device list to override tensors.
* rpc : prevent crashes on invalid input (#9040)
Add more checks which prevent RPC server from crashing if invalid input
is received from client
# Conflicts:
# ggml/src/ggml-rpc.cpp
* rpc : print error message when failed to connect endpoint (#9042)
* Fix RPC error
* Add vulkan, sycl to rpc backend
* add thread in rpc cpu backend
* add cache folder and other improvement in rpc
* add header file
* support for models with non-512 aligned tensors
* rpc : do not wait for response when sending RPC_CMD_SET_TENSOR (#12943)
RPC_CMD_SET_TENSOR always returns an empty response and we send this 4
times per token. We can improve TG speed if we don't wait for this empty
response.
The performance impact of this change depends on the network latency.
# Conflicts:
# ggml/src/ggml-rpc.cpp
* fix(rpc): Improve input validation and error handling (#13069)
* fix(rpc): Improve input validation and error handling
The `rpc-server` was vulnerable to Denial of Service attacks via
several RPC commands (`SET_TENSOR`, `GRAPH_COMPUTE`, etc.). Malformed
messages could trigger failed assertions (e.g., invalid `ggml_type`)
or out-of-bounds reads/writes leading to `GGML_ABORT` calls,
crashing the server process.
This PR introduces robust input validation and replaces `abort()`
calls with graceful error handling:
- **Type Validation:** `deserialize_tensor` now checks if the
`tensor->type` is within the valid `GGML_TYPE_COUNT` range
*before* calling `ggml_new_tensor_4d`. Returns `nullptr` on
invalid type.
- **Bounds Checks:** Replaced `GGML_ABORT` in `set_tensor`,
`set_tensor_hash`, and `get_tensor` handlers with error
logging and returning `false` when data/offset parameters
are out of buffer bounds.
- **Size Checks:** Added safe arithmetic checks (for overflow) in
`graph_compute` when calculating required message sizes based
on client-provided `n_nodes` and `n_tensors`. Returns early
if the reported sizes conflict with the actual message size or
would lead to overflow.
- **Error Propagation:**
- `create_node` now checks for `nullptr` return values from
`deserialize_tensor` and its recursive calls, propagating
`nullptr` upwards on failure. Uses `find` instead of `at`
for safer map access.
- `copy_tensor` now checks for `nullptr` from `deserialize_tensor`
and sets the response status to failure if deserialization
or bounds checks fail.
- `graph_compute` now checks for `nullptr` return from
`create_node` and returns failure status correctly. The final
return value now reflects the actual computation status.
These changes improve the RPC server's resilience
against malformed client requests, preventing crashes and ensuring
errors are handled more gracefully.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): address pr comments
removed comments and unnecessary returns
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): ambiguous nullptr from create_node
rpc_server::create_node could previously return nullptr if the input ID
was 0 (valid) or if an internal error (deserialization, recursion
failure) occurred (invalid). This ambiguity made error handling
difficult for the caller (`graph_compute`).
This commit clarifies the meaning of nullptr:
- `graph_compute` now checks if the input 'id' was non-zero when
`create_node` returns nullptr, correctly identifying failures
versus intentional null links.
- `create_node` avoids recursive calls for zero IDs and propagates
nullptr unambiguously on failure during recursion.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): initial zero check in create_node
The caller (`graph_compute`) already checks `id != 0` when handling
a `nullptr` return from `create_node`, correctly distinguishing
intentional null links from actual errors. This makes the initial
`if (id == 0)` check redundant.
Also removes the log message when a tensor ID is not found in the
provided map which was added in this branch.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* fix(rpc): Handle get_alloc_size failure in server
Check the return value of `server.get_alloc_size` in the RPC server
loop. If the call fails, return early to close the connection.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): input size validation in graph_compute
Removes detailed, step-by-step size calculations and overflow
checks in favor of simpler direct comparisons, assuming 64-bit
overflow is unlikely.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): remove extra status code setting
Removes the explicit setting of `response.result = GGML_STATUS_FAILED`
when `create_node` returns `nullptr` within `graph_compute`.
Primary signal is the `false` return value in case of failure.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): remove redundant check for tensor->type
Breaks CI on ubuntu-cpu-make. Tensor type is uint32_t, thus
the check is not needed.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
---------
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
# Conflicts:
# ggml/src/ggml-rpc.cpp
* rpc : fix cache directory initialization (#13188)
Signed-off-by: xiaofei <hbuxiaofei@gmail.com>
# Conflicts:
# examples/rpc/rpc-server.cpp
* rpc : avoid uninitialized memory in serialize_tensor (#13210)
Zero out the name and padding buffers.
* fix merge error
* Add hello command in RPC
* bug fix
* add rpc header
* fix bug for missing rpc names
* add tpc no delay for rpc
* add back webui
* fix rpc function not found error
---------
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
Signed-off-by: xiaofei <hbuxiaofei@gmail.com>
Co-authored-by: firecoperana <firecoperana>
Co-authored-by: Radoslav Gerganov <rgerganov@gmail.com>
Co-authored-by: matt23456 <matt23456>
Co-authored-by: Ville Vesilehto <ville@vesilehto.fi>
Co-authored-by: xiaofei <hbuxiaofei@gmail.com>
Co-authored-by: Justin Santa Barbara <justinsb@google.com>
* Add RPC backend in device list to override tensors.
* rpc : prevent crashes on invalid input (#9040)
Add more checks which prevent RPC server from crashing if invalid input
is received from client
# Conflicts:
# ggml/src/ggml-rpc.cpp
* rpc : print error message when failed to connect endpoint (#9042)
* Fix RPC error
* Add vulkan, sycl to rpc backend
* add thread in rpc cpu backend
* add cache folder and other improvement in rpc
* add header file
* support for models with non-512 aligned tensors
* rpc : do not wait for response when sending RPC_CMD_SET_TENSOR (#12943)
RPC_CMD_SET_TENSOR always returns an empty response and we send this 4
times per token. We can improve TG speed if we don't wait for this empty
response.
The performance impact of this change depends on the network latency.
# Conflicts:
# ggml/src/ggml-rpc.cpp
* fix(rpc): Improve input validation and error handling (#13069)
* fix(rpc): Improve input validation and error handling
The `rpc-server` was vulnerable to Denial of Service attacks via
several RPC commands (`SET_TENSOR`, `GRAPH_COMPUTE`, etc.). Malformed
messages could trigger failed assertions (e.g., invalid `ggml_type`)
or out-of-bounds reads/writes leading to `GGML_ABORT` calls,
crashing the server process.
This PR introduces robust input validation and replaces `abort()`
calls with graceful error handling:
- **Type Validation:** `deserialize_tensor` now checks if the
`tensor->type` is within the valid `GGML_TYPE_COUNT` range
*before* calling `ggml_new_tensor_4d`. Returns `nullptr` on
invalid type.
- **Bounds Checks:** Replaced `GGML_ABORT` in `set_tensor`,
`set_tensor_hash`, and `get_tensor` handlers with error
logging and returning `false` when data/offset parameters
are out of buffer bounds.
- **Size Checks:** Added safe arithmetic checks (for overflow) in
`graph_compute` when calculating required message sizes based
on client-provided `n_nodes` and `n_tensors`. Returns early
if the reported sizes conflict with the actual message size or
would lead to overflow.
- **Error Propagation:**
- `create_node` now checks for `nullptr` return values from
`deserialize_tensor` and its recursive calls, propagating
`nullptr` upwards on failure. Uses `find` instead of `at`
for safer map access.
- `copy_tensor` now checks for `nullptr` from `deserialize_tensor`
and sets the response status to failure if deserialization
or bounds checks fail.
- `graph_compute` now checks for `nullptr` return from
`create_node` and returns failure status correctly. The final
return value now reflects the actual computation status.
These changes improve the RPC server's resilience
against malformed client requests, preventing crashes and ensuring
errors are handled more gracefully.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): address pr comments
removed comments and unnecessary returns
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): ambiguous nullptr from create_node
rpc_server::create_node could previously return nullptr if the input ID
was 0 (valid) or if an internal error (deserialization, recursion
failure) occurred (invalid). This ambiguity made error handling
difficult for the caller (`graph_compute`).
This commit clarifies the meaning of nullptr:
- `graph_compute` now checks if the input 'id' was non-zero when
`create_node` returns nullptr, correctly identifying failures
versus intentional null links.
- `create_node` avoids recursive calls for zero IDs and propagates
nullptr unambiguously on failure during recursion.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): initial zero check in create_node
The caller (`graph_compute`) already checks `id != 0` when handling
a `nullptr` return from `create_node`, correctly distinguishing
intentional null links from actual errors. This makes the initial
`if (id == 0)` check redundant.
Also removes the log message when a tensor ID is not found in the
provided map which was added in this branch.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* fix(rpc): Handle get_alloc_size failure in server
Check the return value of `server.get_alloc_size` in the RPC server
loop. If the call fails, return early to close the connection.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): input size validation in graph_compute
Removes detailed, step-by-step size calculations and overflow
checks in favor of simpler direct comparisons, assuming 64-bit
overflow is unlikely.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): remove extra status code setting
Removes the explicit setting of `response.result = GGML_STATUS_FAILED`
when `create_node` returns `nullptr` within `graph_compute`.
Primary signal is the `false` return value in case of failure.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
* refactor(rpc): remove redundant check for tensor->type
Breaks CI on ubuntu-cpu-make. Tensor type is uint32_t, thus
the check is not needed.
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
---------
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
# Conflicts:
# ggml/src/ggml-rpc.cpp
* rpc : fix cache directory initialization (#13188)
Signed-off-by: xiaofei <hbuxiaofei@gmail.com>
# Conflicts:
# examples/rpc/rpc-server.cpp
* rpc : avoid uninitialized memory in serialize_tensor (#13210)
Zero out the name and padding buffers.
* fix merge error
* Add hello command in RPC
* bug fix
* add rpc header
* fix bug for missing rpc names
* add tpc no delay for rpc
* add back webui
---------
Signed-off-by: Ville Vesilehto <ville@vesilehto.fi>
Signed-off-by: xiaofei <hbuxiaofei@gmail.com>
Co-authored-by: firecoperana <firecoperana>
Co-authored-by: Radoslav Gerganov <rgerganov@gmail.com>
Co-authored-by: matt23456 <matt23456>
Co-authored-by: Ville Vesilehto <ville@vesilehto.fi>
Co-authored-by: xiaofei <hbuxiaofei@gmail.com>
Co-authored-by: Justin Santa Barbara <justinsb@google.com>
I cannot possibly wait for a 5 minutes nvcc compilation
each time I touch vecdotq.cuh.
Also, cmake was adding --options-file X.rsp to the nvcc
compile commands, which confuses clangd, so I have turned
that off.
* Merging mainline - WIP
* Merging mainline - WIP
AVX2 and CUDA appear to work.
CUDA performance seems slightly (~1-2%) lower as it is so often
the case with llama.cpp/ggml after some "improvements" have been made.
* Merging mainline - fix Metal
* Remove check
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
* separate DPCT helpers outside
* replace global variables with context
* remove useless extra
* update mul_mat condition
* remove duplicate buft initialization
* remove duplicate extra and global work group size
* remove useless backend check
* remove duplicated extras
* use macro for group_size and remove cuda-related
* move BLAS to a separate backend
* rename GGML_USE_OPENBLAS to GGML_USE_BLAS
* alloc : reuse same buffer when the same buffer type if used multiple times
* set number of threads automatically for openblas and blis
* sched : print assignments when GGML_SCHED_DEBUG env variable is set
* sched : allow ops with weights on an incompatible buffer type
This will cause the weight to be copied to a backend that supports the
op, which is very costly. The weight should have been stored in a buffer
of a backend that can run the op, but llama.cpp cannot do this
automatically at the moment.
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Improve hipBLAS support in CMake
This improves the detection of the correct CMAKE_PREFIX_PATH when using different distributions or a self-built ROCm SDK.
* Set ROCM_PATH correctly
* ggml: Added OpenMP for multi-threads processing
* ggml : Limit the number of threads used to avoid deadlock
* update shared state n_threads in parallel region
* clear numa affinity for main thread even with openmp
* enable openmp by default
* fix msvc build
* disable openmp on macos
* ci : disable openmp with thread sanitizer
* Update ggml.c
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: slaren <slarengh@gmail.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
op_getrows_f32 is required since https://github.com/ggerganov/llama.cpp/pull/6122
for the Vulkan w/ Kompute backend to be functional.
As such, implement this op to make this backend functional again.
Supercedes #4024 and #4813.
CMake's native HIP support has become the
recommended way to add HIP code into a project (see
[here](https://rocm.docs.amd.com/en/docs-6.0.0/conceptual/cmake-packages.html#using-hip-in-cmake)).
This PR makes the following changes:
1. The environment variable `HIPCXX` or CMake option
`CMAKE_HIP_COMPILER` should be used to specify the HIP
compiler. Notably this shouldn't be `hipcc`, but ROCm's clang,
which usually resides in `$ROCM_PATH/llvm/bin/clang`. Previously
this was control by `CMAKE_C_COMPILER` and `CMAKE_CXX_COMPILER`.
Note that since native CMake HIP support is not yet available on
Windows, on Windows we fall back to the old behavior.
2. CMake option `CMAKE_HIP_ARCHITECTURES` is used to control the
GPU architectures to build for. Previously this was controled by
`GPU_TARGETS`.
3. Updated the Nix recipe to account for these new changes.
4. The GPU targets to build against in the Nix recipe is now
consistent with the supported GPU targets in nixpkgs.
5. Added CI checks for HIP on both Linux and Windows. On Linux, we test
both the new and old behavior.
The most important part about this PR is the separation of the
HIP compiler and the C/C++ compiler. This allows users to choose
a different C/C++ compiler if desired, compared to the current
situation where when building for ROCm support, everything must be
compiled with ROCm's clang.
~~Makefile is unchanged. Please let me know if we want to be
consistent on variables' naming because Makefile still uses
`GPU_TARGETS` to control architectures to build for, but I feel
like setting `CMAKE_HIP_ARCHITECTURES` is a bit awkward when you're
calling `make`.~~ Makefile used `GPU_TARGETS` but the README says
to use `AMDGPU_TARGETS`. For consistency with CMake, all usage of
`GPU_TARGETS` in Makefile has been updated to `AMDGPU_TARGETS`.
Thanks to the suggestion of @jin-eld, to maintain backwards
compatibility (and not break too many downstream users' builds), if
`CMAKE_CXX_COMPILER` ends with `hipcc`, then we still compile using
the original behavior and emit a warning that recommends switching
to the new HIP support. Similarly, if `AMDGPU_TARGETS` is set but
`CMAKE_HIP_ARCHITECTURES` is not, then we forward `AMDGPU_TARGETS`
to `CMAKE_HIP_ARCHITECTURES` to ease the transition to the new
HIP support.
Signed-off-by: Gavin Zhao <git@gzgz.dev>
* logging: add proper checks for clang to avoid errors and warnings with VA_ARGS
* build: add CMake Presets and toolchian files for Windows ARM64
* matmul-int8: enable matmul-int8 with MSVC and fix Clang warnings
* ci: add support for optimized Windows ARM64 builds with MSVC and LLVM
* matmul-int8: fixed typos in q8_0_q8_0 matmuls
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* matmul-int8: remove unnecessary casts in q8_0_q8_0
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* DRAFT: Introduction of CUDA Graphs to LLama.cpp
* FIx issues raised in comments
* Tidied to now only use CUDA runtime (not mixed with driver calls)
* disable for multi-gpu and batch size > 1
* Disable CUDA graphs for old GPU arch and with env var
* added missing CUDA_CHECKs
* Addressed comments
* further addressed comments
* limit to GGML_ALLOW_CUDA_GRAPHS defined in llama.cpp cmake
* Added more comprehensive graph node checking
* With mechanism to fall back if graph capture fails
* Revert "With mechanism to fall back if graph capture fails"
This reverts commit eb9f15fb6fcb81384f732c4601a5b25c016a5143.
* Fall back if graph capture fails and address other comments
* - renamed GGML_ALLOW_CUDA_GRAPHS to GGML_CUDA_USE_GRAPHS
- rename env variable to disable CUDA graphs to GGML_CUDA_DISABLE_GRAPHS
- updated Makefile build to enable CUDA graphs
- removed graph capture failure checking in ggml_cuda_error
using a global variable to track this is not thread safe, but I am also not safistied with checking an error by string
if this is necessary to workaround some issues with graph capture with eg. cuBLAS, we can pass the ggml_backend_cuda_context to the error checking macro and store the result in the context
- fixed several resource leaks
- fixed issue with zero node graphs
- changed fixed size arrays to vectors
- removed the count of number of evaluations before start capturing, and instead changed the capture mode to relaxed
- removed the check for multiple devices so that it is still possible to use a single device, instead checks for split buffers to disable cuda graphs with -sm row
- changed the op for checking batch size to GGML_OP_ADD, should be more reliable than GGML_OP_SOFT_MAX
- code style fixes
- things to look into
- VRAM usage of the cudaGraphExec_t, if it is significant we may need to make it optional
- possibility of using cudaStreamBeginCaptureToGraph to keep track of which ggml graph nodes correspond to which cuda graph nodes
* fix build without cuda graphs
* remove outdated comment
* replace minimum cc value with a constant
---------
Co-authored-by: slaren <slarengh@gmail.com>
* 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
