cuda linux

llama/README.md

@@ -6,11 +6,10 @@ Supported:
 
 - [x] CPU
 - [x] avx, avx2
-- [ ] avx512
 - [x] macOS Metal
 - [x] Windows CUDA
 - [x] Windows ROCm
-- [ ] Linux CUDA
+- [x] Linux CUDA
 - [ ] Linux ROCm
 - [x] Llava
 - [ ] Parallel Requests
@@ -44,14 +43,32 @@ go env -w "CGO_CXXFLAGS_ALLOW=-mfma|-mf16c"
 go build -tags=avx,avx2 .
 ```
 
+## Linux
+
 ### CUDA
 
-Install the [CUDA toolkit v11.3.1](https://developer.nvidia.com/cuda-11-3-1-download-archive) then build ggml-cuda:
+Install the [CUDA toolkit v11.3.1](https://developer.nvidia.com/cuda-11-3-1-download-archive) then build `libggml-cuda.so`:
+
+```shell
+./build_cuda.sh
+```
+
+Then build the package with the `cuda` tag:
+
+```shell
+go build -tags=cuda .
+```
+
+## Windows
+
+### CUDA
+
+Install the [CUDA toolkit v11.3.1](https://developer.nvidia.com/cuda-11-3-1-download-archive) then build the cuda code:
 
 Build `ggml-cuda.dll`:
 
 ```shell
-./build_cuda.sh
+./build_cuda.ps1
 ```
 
 Then build the package with the `cuda` tag:

llama/build_cuda.ps1

@@ -0,0 +1,24 @@
+nvcc -t 12 `
+    --generate-code=arch=compute_50,code=[compute_50,sm_50] `
+    --generate-code=arch=compute_52,code=[compute_52,sm_52] `
+    --generate-code=arch=compute_61,code=[compute_61,sm_61] `
+    --generate-code=arch=compute_70,code=[compute_70,sm_70] `
+    --generate-code=arch=compute_75,code=[compute_75,sm_75] `
+    --generate-code=arch=compute_80,code=[compute_80,sm_80] `
+    -DGGML_CUDA_DMMV_X=32 `
+    -DGGML_CUDA_PEER_MAX_BATCH_SIZE=128 `
+    -DGGML_CUDA_MMV_Y=1 `
+    -DGGML_USE_CUDA=1 `
+    -DGGML_SHARED=1 `
+    -DGGML_BUILD=1 `
+    -DGGML_USE_LLAMAFILE `
+    -Wno-deprecated-gpu-targets `
+    --forward-unknown-to-host-compiler `
+    -use_fast_math `
+    -link `
+    -shared `
+    -I. `
+    -lcuda -lcublas -lcudart -lcublasLt `
+    -O3 `
+    -o ggml-cuda.dll `
+    ggml-cuda.cu ggml-cuda/*.cu ggml.c ggml-backend.c ggml-alloc.c ggml-quants.c sgemm.cpp

llama/build_cuda.sh

@@ -8,19 +8,20 @@ nvcc \
     --generate-code=arch=compute_80,code=[compute_80,sm_80] \
     -DGGML_CUDA_DMMV_X=32 \
     -DGGML_CUDA_PEER_MAX_BATCH_SIZE=128 \
-    -DGGML_MULTIPLATFORM \
     -DGGML_CUDA_MMV_Y=1 \
     -DGGML_USE_CUDA=1 \
     -DGGML_SHARED=1 \
     -DGGML_BUILD=1 \
     -DGGML_USE_LLAMAFILE \
+    -D_GNU_SOURCE \
     -Wno-deprecated-gpu-targets \
     --forward-unknown-to-host-compiler \
     -use_fast_math \
     -link \
     -shared \
+    -fPIC \
     -I. \
     -lcuda -lcublas -lcudart -lcublasLt \
     -O3 \
-    -o ggml-cuda.dll \
+    -o libggml-cuda.so \
     ggml-cuda.cu ggml-cuda/*.cu ggml.c ggml-backend.c ggml-alloc.c ggml-quants.c sgemm.cpp

llama/llama.go

@@ -8,16 +8,19 @@ package llama
 // #cgo darwin,amd64 CFLAGS: -Wno-incompatible-pointer-types-discards-qualifiers
 // #cgo darwin,amd64 CXXFLAGS: -Wno-incompatible-pointer-types-discards-qualifiers
 // #cgo darwin,amd64 LDFLAGS: -ld_classic -framework Foundation -framework Accelerate
+// #cgo linux CFLAGS: -D_GNU_SOURCE
+// #cgo linux CXXFLAGS: -D_GNU_SOURCE
 // #cgo windows LDFLAGS: -lmsvcrt
 // #cgo avx CFLAGS: -mavx
 // #cgo avx CXXFLAGS: -mavx
 // #cgo avx2 CFLAGS: -mavx2 -mfma
 // #cgo avx2 CXXFLAGS: -mavx2 -mfma
-// #cgo cuda CFLAGS: -DGGML_USE_CUDA -DGGML_CUDA_DMMV_X=32 -DGGML_CUDA_PEER_MAX_BATCH_SIZE=128 -DGGML_MULTIPLATFORM -DGGML_CUDA_MMV_Y=1 -DGGML_BUILD=1
+// #cgo cuda CFLAGS: -DGGML_USE_CUDA -DGGML_CUDA_DMMV_X=32 -DGGML_CUDA_PEER_MAX_BATCH_SIZE=128 -DGGML_CUDA_MMV_Y=1 -DGGML_BUILD=1
-// #cgo cuda CXXFLAGS: -DGGML_USE_CUDA -DGGML_CUDA_DMMV_X=32 -DGGML_CUDA_PEER_MAX_BATCH_SIZE=128 -DGGML_MULTIPLATFORM -DGGML_CUDA_MMV_Y=1 -DGGML_BUILD=1
+// #cgo cuda CXXFLAGS: -DGGML_USE_CUDA -DGGML_CUDA_DMMV_X=32 -DGGML_CUDA_PEER_MAX_BATCH_SIZE=128 -DGGML_CUDA_MMV_Y=1 -DGGML_BUILD=1
 // #cgo rocm CXXFLAGS: -DGGML_USE_CUDA -DGGML_USE_HIPBLAS -DGGML_CUDA_DMMV_X=32 -DGGML_CUDA_PEER_MAX_BATCH_SIZE=128 -DGGML_MULTIPLATFORM -DGGML_CUDA_MMV_Y=1 -DGGML_BUILD=1
 // #cgo windows,cuda LDFLAGS: -L. -L"C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v11.3/lib/x64" -lggml-cuda -lcuda -lcudart -lcublas -lcublasLt
 // #cgo windows,rocm LDFLAGS: -L. -L"C:/Program Files/AMD/ROCm/5.7/lib" -lggml-hipblas -lhipblas -lamdhip64 -lrocblas
+// #cgo linux,cuda LDFLAGS: -L${SRCDIR} -L/usr/local/cuda/lib64 -lggml-cuda -lcuda -lcudart -lcublas -lcublasLt -lpthread -ldl -lrt
 // #include <stdlib.h>
 // #include "llama.h"
 // #include "clip.h"