feat(krz01): move the GPU stuff to the host for now
We also add a K80 specific patch for ollama. Signed-off-by: Ryan Lahfa <ryan@dgnum.eu>
This commit is contained in:
parent
8160b2762f
commit
4bedb3f497
3 changed files with 213 additions and 44 deletions
179
machines/krz01/K80-support.patch
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179
machines/krz01/K80-support.patch
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@ -0,0 +1,179 @@
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From 2abd226ff3093c5a9e18a618fba466853e7ebaf7 Mon Sep 17 00:00:00 2001
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From: Raito Bezarius <masterancpp@gmail.com>
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Date: Tue, 8 Oct 2024 18:27:41 +0200
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Subject: [PATCH] K80 support
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Signed-off-by: Raito Bezarius <masterancpp@gmail.com>
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---
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docs/development.md | 6 +++-
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docs/gpu.md | 1 +
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gpu/amd_linux.go | 6 +++-
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gpu/gpu.go | 63 ++++++++++++++++++++++++++++++++++++-----
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scripts/build_docker.sh | 2 +-
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scripts/build_linux.sh | 2 +-
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6 files changed, 69 insertions(+), 11 deletions(-)
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diff --git a/docs/development.md b/docs/development.md
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index 2f7b9ecf..9da35931 100644
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--- a/docs/development.md
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+++ b/docs/development.md
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@@ -51,7 +51,11 @@ Typically the build scripts will auto-detect CUDA, however, if your Linux distro
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or installation approach uses unusual paths, you can specify the location by
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specifying an environment variable `CUDA_LIB_DIR` to the location of the shared
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libraries, and `CUDACXX` to the location of the nvcc compiler. You can customize
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-a set of target CUDA architectures by setting `CMAKE_CUDA_ARCHITECTURES` (e.g. "50;60;70")
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+a set of target CUDA architectures by setting `CMAKE_CUDA_ARCHITECTURES` (e.g. "35;37;50;60;70")
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+
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+To support GPUs older than Compute Capability 5.0, you will need to use an older version of
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+the Driver from [Unix Driver Archive](https://www.nvidia.com/en-us/drivers/unix/) (tested with 470) and [CUDA Toolkit Archive](https://developer.nvidia.com/cuda-toolkit-archive) (tested with cuda V11). When you build Ollama, you will need to set two environment variable to adjust the minimum compute capability Ollama supports via `export GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/gpu.CudaComputeMajorMin=3\" \"-X=github.com/ollama/ollama/gpu.CudaComputeMinorMin=5\"'"` and the `CMAKE_CUDA_ARCHITECTURES`. To find the Compute Capability of your older GPU, refer to [GPU Compute Capability](https://developer.nvidia.com/cuda-gpus).
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+
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Then generate dependencies:
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diff --git a/docs/gpu.md b/docs/gpu.md
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index a6b559f0..66627611 100644
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--- a/docs/gpu.md
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+++ b/docs/gpu.md
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@@ -28,6 +28,7 @@ Check your compute compatibility to see if your card is supported:
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| 5.0 | GeForce GTX | `GTX 750 Ti` `GTX 750` `NVS 810` |
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| | Quadro | `K2200` `K1200` `K620` `M1200` `M520` `M5000M` `M4000M` `M3000M` `M2000M` `M1000M` `K620M` `M600M` `M500M` |
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+For building locally to support older GPUs, see [developer.md](./development.md#linux-cuda-nvidia)
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### GPU Selection
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diff --git a/gpu/amd_linux.go b/gpu/amd_linux.go
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index 6b08ac2e..768fb97a 100644
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--- a/gpu/amd_linux.go
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+++ b/gpu/amd_linux.go
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@@ -159,7 +159,11 @@ func AMDGetGPUInfo() []GpuInfo {
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return []GpuInfo{}
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}
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- if int(major) < RocmComputeMin {
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+ minVer, err := strconv.Atoi(RocmComputeMajorMin)
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+ if err != nil {
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+ slog.Error("invalid RocmComputeMajorMin setting", "value", RocmComputeMajorMin, "error", err)
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+ }
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+ if int(major) < minVer {
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slog.Warn(fmt.Sprintf("amdgpu too old gfx%d%x%x", major, minor, patch), "gpu", gpuID)
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continue
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}
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diff --git a/gpu/gpu.go b/gpu/gpu.go
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index 781e23df..60d68c33 100644
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--- a/gpu/gpu.go
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+++ b/gpu/gpu.go
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@@ -16,6 +16,7 @@ import (
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"os"
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"path/filepath"
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"runtime"
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+ "strconv"
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"strings"
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"sync"
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"unsafe"
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@@ -38,9 +39,11 @@ const (
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var gpuMutex sync.Mutex
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// With our current CUDA compile flags, older than 5.0 will not work properly
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-var CudaComputeMin = [2]C.int{5, 0}
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+// (string values used to allow ldflags overrides at build time)
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+var CudaComputeMajorMin = "5"
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+var CudaComputeMinorMin = "0"
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-var RocmComputeMin = 9
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+var RocmComputeMajorMin = "9"
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// TODO find a better way to detect iGPU instead of minimum memory
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const IGPUMemLimit = 1 * format.GibiByte // 512G is what they typically report, so anything less than 1G must be iGPU
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@@ -175,11 +178,57 @@ func GetGPUInfo() GpuInfoList {
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var memInfo C.mem_info_t
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resp := []GpuInfo{}
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- // NVIDIA first
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- for i := 0; i < gpuHandles.deviceCount; i++ {
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- // TODO once we support CPU compilation variants of GPU libraries refine this...
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- if cpuVariant == "" && runtime.GOARCH == "amd64" {
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- continue
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+ // Load ALL libraries
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+ cHandles = initCudaHandles()
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+ minMajorVer, err := strconv.Atoi(CudaComputeMajorMin)
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+ if err != nil {
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+ slog.Error("invalid CudaComputeMajorMin setting", "value", CudaComputeMajorMin, "error", err)
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+ }
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+ minMinorVer, err := strconv.Atoi(CudaComputeMinorMin)
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+ if err != nil {
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+ slog.Error("invalid CudaComputeMinorMin setting", "value", CudaComputeMinorMin, "error", err)
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+ }
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+
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+ // NVIDIA
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+ for i := range cHandles.deviceCount {
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+ if cHandles.cudart != nil || cHandles.nvcuda != nil {
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+ gpuInfo := CudaGPUInfo{
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+ GpuInfo: GpuInfo{
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+ Library: "cuda",
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+ },
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+ index: i,
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+ }
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+ var driverMajor int
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+ var driverMinor int
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+ if cHandles.cudart != nil {
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+ C.cudart_bootstrap(*cHandles.cudart, C.int(i), &memInfo)
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+ } else {
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+ C.nvcuda_bootstrap(*cHandles.nvcuda, C.int(i), &memInfo)
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+ driverMajor = int(cHandles.nvcuda.driver_major)
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+ driverMinor = int(cHandles.nvcuda.driver_minor)
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+ }
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+ if memInfo.err != nil {
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+ slog.Info("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
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+ C.free(unsafe.Pointer(memInfo.err))
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+ continue
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+ }
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+
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+ if int(memInfo.major) < minMajorVer || (int(memInfo.major) == minMajorVer && int(memInfo.minor) < minMinorVer) {
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+ slog.Info(fmt.Sprintf("[%d] CUDA GPU is too old. Compute Capability detected: %d.%d", i, memInfo.major, memInfo.minor))
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+ continue
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+ }
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+ gpuInfo.TotalMemory = uint64(memInfo.total)
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+ gpuInfo.FreeMemory = uint64(memInfo.free)
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+ gpuInfo.ID = C.GoString(&memInfo.gpu_id[0])
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+ gpuInfo.Compute = fmt.Sprintf("%d.%d", memInfo.major, memInfo.minor)
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+ gpuInfo.MinimumMemory = cudaMinimumMemory
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+ gpuInfo.DependencyPath = depPath
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+ gpuInfo.Name = C.GoString(&memInfo.gpu_name[0])
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+ gpuInfo.DriverMajor = driverMajor
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+ gpuInfo.DriverMinor = driverMinor
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+
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+ // TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
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+ cudaGPUs = append(cudaGPUs, gpuInfo)
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}
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gpuInfo := GpuInfo{
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Library: "cuda",
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diff --git a/scripts/build_docker.sh b/scripts/build_docker.sh
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index e91c56ed..c03bc25f 100755
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--- a/scripts/build_docker.sh
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+++ b/scripts/build_docker.sh
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@@ -3,7 +3,7 @@
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set -eu
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export VERSION=${VERSION:-$(git describe --tags --first-parent --abbrev=7 --long --dirty --always | sed -e "s/^v//g")}
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-export GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=$VERSION\" \"-X=github.com/ollama/ollama/server.mode=release\"'"
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+export GOFLAGS=${GOFLAGS:-"'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=$VERSION\" \"-X=github.com/ollama/ollama/server.mode=release\"'"}
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# We use 2 different image repositories to handle combining architecture images into multiarch manifest
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# (The ROCm image is x86 only and is not a multiarch manifest)
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diff --git a/scripts/build_linux.sh b/scripts/build_linux.sh
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index 27c4ff1f..e7e6d0dd 100755
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--- a/scripts/build_linux.sh
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+++ b/scripts/build_linux.sh
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@@ -3,7 +3,7 @@
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set -eu
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export VERSION=${VERSION:-$(git describe --tags --first-parent --abbrev=7 --long --dirty --always | sed -e "s/^v//g")}
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-export GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=$VERSION\" \"-X=github.com/ollama/ollama/server.mode=release\"'"
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+export GOFLAGS=${GOFLAGS:-"'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=$VERSION\" \"-X=github.com/ollama/ollama/server.mode=release\"'"}
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BUILD_ARCH=${BUILD_ARCH:-"amd64 arm64"}
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export AMDGPU_TARGETS=${AMDGPU_TARGETS:=""}
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--
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2.46.0
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@ -1,4 +1,4 @@
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{ lib, ... }:
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{ lib, pkgs, ... }:
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lib.extra.mkConfig {
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lib.extra.mkConfig {
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enabledModules = [
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enabledModules = [
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@ -30,7 +30,23 @@ lib.extra.mkConfig {
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# We are going to use CUDA here.
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# We are going to use CUDA here.
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nixpkgs.config.cudaSupport = true;
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nixpkgs.config.cudaSupport = true;
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services.ollama = {
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enable = true;
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package =
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(pkgs.ollama.override {
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cudaPackages = pkgs.cudaPackages_11;
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gcc12 = pkgs.gcc11;
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}).overrideAttrs
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(old: {
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CMAKE_CUDA_ARCHITECTURES = "35";
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ldflags = old.ldflags ++ [
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# K80 is 3.5
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"-X=github.com/ollama/ollama/gpu.CudaComputeMajorMin=3"
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"-X=github.com/ollama/ollama/gpu.CudaComputeMinorMin=5"
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];
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patches = (old.patches or [ ]) ++ [ ./K80-support.patch ];
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});
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};
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users.users.root.hashedPassword = "$y$j9T$eNZQgDN.J5y7KTG2hXgat1$J1i5tjx5dnSZu.C9B7swXi5zMFIkUnmRrnmyLHFAt8/";
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users.users.root.hashedPassword = "$y$j9T$eNZQgDN.J5y7KTG2hXgat1$J1i5tjx5dnSZu.C9B7swXi5zMFIkUnmRrnmyLHFAt8/";
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};
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};
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@ -1,39 +1,13 @@
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_: {
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_: {
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microvm.autostart = [ "ml01" ];
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microvm.autostart = [ "ml01" ];
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microvm.vms.ml01 = {
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microvm.vms.ml01 = {
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config =
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config = {
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{ config, ... }:
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{
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nixpkgs.config.cudaSupport = true;
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nixpkgs.config.nvidia.acceptLicense = true;
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# Tesla K80 is not supported by the latest driver.
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hardware.nvidia.package = config.boot.kernelPackages.nvidia_x11_legacy470;
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# Don't ask.
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services.xserver.videoDrivers = [ "nvidia" ];
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networking.hostName = "ml01";
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networking.hostName = "ml01";
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services.ollama = {
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enable = true;
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listenAddress = "0.0.0.0:11434";
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sandbox = true;
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acceleration = "cuda";
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};
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microvm = {
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microvm = {
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hypervisor = "cloud-hypervisor";
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hypervisor = "cloud-hypervisor";
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vcpu = 4;
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vcpu = 4;
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mem = 4096;
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mem = 4096;
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balloonMem = 2048;
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balloonMem = 2048;
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devices = [
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# The nVidia Tesla K80
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{
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bus = "pci";
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path = "0000:44:00.0";
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}
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{
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bus = "pci";
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path = "0000:45:00.0";
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}
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];
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shares = [
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shares = [
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{
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{
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source = "/nix/store";
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source = "/nix/store";
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Loading…
Reference in a new issue