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Lataa llama.cpp b10293

LLM inference in C/C++

Tämä on vanhempi versio. Uusin versio on b9994. llama.cpp b9994 · Julkaistu:

Asennustiedostot b10293

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64-bittinen ZIP → Portable — — github.com VirusTotal

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Muutosloki

ci : onboard AMD ROCm CI with gfx1151 fixes (#26544)
- ci: prepare for amd rocm ci
Signed-off-by: Aaron Teo aaron.teo1@ibm.com
- ci: fix editorconfig-checker
Signed-off-by: Aaron Teo aaron.teo1@ibm.com
- ci: fix device not recognised
Signed-off-by: Aaron Teo aaron.teo1@ibm.com
- ci: rename gpu-amd to gpu-hip
Signed-off-by: Aaron Teo aaron.teo1@ibm.com
- ci: gpu-hip to gpu-rocm
haha
Signed-off-by: Aaron Teo aaron.teo1@ibm.com
- CUDA: allow integrated-GPU host output buffer in debug assert
On integrated GPUs (APUs), the scheduler can legitimately place a graph
node's output on the host-visible buffer, which ggml_cuda_compute_forward
already handles. The debug assert in ggml_cuda_graph_evaluate_and_capture
required every node output to be on the device buffer, so a debug build
aborts on such a node (e.g. attn_residual ADD -> ROCm_Host on RDNA3.5).
The source-tensor assert directly below already permits this via the
integrated + cuda_host exception; apply the same exception to the node's
own output buffer. Debug-only; no effect on release/compute.
Fixes test-recurrent-state-rollback on gfx1151 (Strix Halo).
- ci: enable unified memory for ROCm gfx1151 job
Work around a coherence issue on integrated RDNA3.5 (gfx1151) where GPU
kernels reading mmap-loaded weights can return incorrect output, which
makes test-llama-archs (and real inference) intermittently wrong.
GGML_CUDA_ENABLE_UNIFIED_MEMORY=1 uses managed memory, which restores
coherence. Remove once the underlying ROCm/HIP issue is fixed.
- test-llama-archs: skip jamba on HIP backend
jamba produces incorrect output (~0.55 NMSE vs CPU) on the HIP backend on
RDNA3.5 (gfx1151); the SSM kernels need separate investigation. Skip it
for now, matching the existing per-backend carve-outs (WebGPU), so the
ROCm CI can run the test for the remaining architectures.
- ci: use HIP_LAUNCH_BLOCKING for ROCm gfx1151 job
The gfx1151 ROCm CI job produced incorrect inference output (qwen3 perplexity ~88 vs ~9.4) due to an async-execution correctness issue in the HIP path. Serializing kernel launches with HIP_LAUNCH_BLOCKING=1 restores correctness. This replaces the earlier GGML_CUDA_ENABLE_UNIFIED_MEMORY workaround, which did not fix batched inference.
- test-backend-sampler: skip top-k subtests on HIP backend
The ROCm backend does not support the TOP_K/ARGSORT op at vocab scale (no CUB; bitonic argsort is capped at ncols <= 1024), so top-k/top-p backend samplers cannot be offloaded. The penalties, set_sampler, mixed, and top_p subtests assert that offload happened, so they fail on HIP. Skip them until TOP_K is supported on the ROCm backend.
- Update tests/test-backend-sampler.cpp
Co-authored-by: Aaron Teo taronaeo@gmail.com
- Update tests/test-backend-sampler.cpp
Co-authored-by: Georgi Gerganov ggerganov@gmail.com
Signed-off-by: Aaron Teo aaron.teo1@ibm.com
Co-authored-by: Aaron Teo aaron.teo1@ibm.com
Co-authored-by: Jim Wu ywu@xilinx.com
Co-authored-by: Aaron Teo taronaeo@gmail.com
Co-authored-by: Georgi Gerganov ggerganov@gmail.com
Website:
- https://llama.app
macOS/iOS:
- macOS Apple Silicon (arm64)
- macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED
- macOS Intel (x64)
- iOS XCFramework
Linux:
- Ubuntu x64 (CPU)
- Ubuntu arm64 (CPU)
- Ubuntu s390x (CPU)
- Ubuntu x64 (Vulkan)
- Ubuntu arm64 (Vulkan)
- Ubuntu x64 (ROCm 7.2)
- Ubuntu x64 (OpenVINO)
- Ubuntu x64 (SYCL FP32)
- Ubuntu x64 (SYCL FP16)
Android:
- Android arm64 (CPU)
Windows:
- Windows x64 (CPU)
- Windows arm64 (CPU)
- Windows arm64 (OpenCL Adreno)
- Windows x64 (CUDA 12) - CUDA 12.4 DLLs
- Windows x64 (CUDA 13) - CUDA 13.3 DLLs
- Windows x64 (Vulkan)
- Windows x64 (OpenVINO)
- Windows x64 (SYCL)
- Windows x64 (HIP)
openEuler:
- DISABLED
- openEuler x86 (310p)
- openEuler x86 (910b, ACL Graph)
- openEuler aarch64 (310p)
- openEuler aarch64 (910b, ACL Graph)
UI:
- UI

https://github.com/ggml-org/llama.cpp/releases/tag/b10293

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