fish-cpp: add Vulkan backend (CUDA on this model went 0% GPU util — try the README's canonical path)

CUDA backend confirmed broken for fish-speech ops on s2.cpp v0.x — alpha,
incomplete op coverage, GPU stays at 0% during generation despite
ggml_cuda_init succeeding. Vulkan was the original README example
(`-v 0`), so likely the more battle-tested path.

Build the image with BOTH backends so we can flip via env without
rebuilding:
* libvulkan-dev + glslc in the build stage (GGML's Vulkan backend
  compiles its shaders with glslc at build time; without it the
  cmake configure silently disables Vulkan).
* libvulkan1 + the libggml-vulkan.so copy in the runtime stage.
* compose env NVIDIA_DRIVER_CAPABILITIES=compute,utility,graphics —
  default nvidia-container-toolkit only mounts compute libs; Vulkan
  needs the graphics ICD (libGLX_nvidia + nvidia_icd.json) too.
* entrypoint reads FISH_CPP_BACKEND (cuda/vulkan/cpu) and selects
  the appropriate -c/-v/no-flag invocation.
* Default backend = vulkan.
This commit is contained in:
2026-04-28 01:43:06 -07:00
parent 8c1088af1f
commit 67813bbef4
3 changed files with 41 additions and 7 deletions
+20 -3
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@@ -17,7 +17,12 @@ ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update && apt-get install -y --no-install-recommends \
git ca-certificates cmake ninja-build build-essential pkg-config \
libvulkan-dev glslc \
&& rm -rf /var/lib/apt/lists/*
# libvulkan-dev = Vulkan headers + loader for build-time linking.
# glslc = GLSL→SPIR-V compiler; GGML's Vulkan backend compiles its
# shaders with this at build time. Without it, the cmake configure
# step disables Vulkan silently.
WORKDIR /src
RUN git clone --recurse-submodules https://github.com/rodrigomatta/s2.cpp.git \
@@ -38,7 +43,14 @@ WORKDIR /src/s2.cpp
RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/lib/libcuda.so \
&& ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/lib/libcuda.so.1 \
&& ldconfig
RUN cmake -G Ninja -B build -DCMAKE_BUILD_TYPE=Release -DS2_CUDA=ON \
# Build with BOTH CUDA and Vulkan backends — runtime selects via the
# entrypoint (-c <id> for CUDA, -v <id> for Vulkan). We've established
# that s2.cpp's CUDA path silently falls back to CPU on this model
# (alpha software, incomplete op coverage); Vulkan is the README's
# canonical example so it likely has more complete op coverage on
# fish-speech. Keep both built so we can flip without rebuilding.
RUN cmake -G Ninja -B build -DCMAKE_BUILD_TYPE=Release \
-DS2_CUDA=ON -DS2_VULKAN=ON \
&& cmake --build build --parallel $(nproc) --target s2
# ── Stage 2: runtime — slim image with the binary + python shim ────────
@@ -51,9 +63,13 @@ ENV DEBIAN_FRONTEND=noninteractive \
RUN apt-get update && apt-get install -y --no-install-recommends \
python3 python3-pip python3-venv tini \
libgomp1 curl \
libvulkan1 \
&& rm -rf /var/lib/apt/lists/*
# libgomp1 = GNU OpenMP runtime — required by the s2 binary.
# curl = entrypoint uses it to wait for s2 server to bind :3030.
# libgomp1 = GNU OpenMP runtime — required by the s2 binary.
# curl = entrypoint uses it to wait for s2 server to bind :3030.
# libvulkan1 = Vulkan loader. The NVIDIA Vulkan ICD itself comes from
# the host driver via NVIDIA container runtime when
# NVIDIA_DRIVER_CAPABILITIES includes "graphics".
# Pull the shim deps into an isolated venv so we don't fight system pip.
RUN python3 -m venv /opt/venv
@@ -64,6 +80,7 @@ RUN pip install --no-cache-dir 'fastapi>=0.115' 'uvicorn[standard]>=0.30' 'pydan
COPY --from=builder /src/s2.cpp/build/s2 /usr/local/bin/s2
COPY --from=builder /src/s2.cpp/build/ggml/src/libggml*.so /usr/local/lib/
COPY --from=builder /src/s2.cpp/build/ggml/src/ggml-cuda/libggml-cuda.so /usr/local/lib/
COPY --from=builder /src/s2.cpp/build/ggml/src/ggml-vulkan/libggml-vulkan.so /usr/local/lib/
RUN ldconfig
WORKDIR /app
+9
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@@ -35,9 +35,18 @@ services:
- "${FISH_CPP_BIND:-0.0.0.0}:${FISH_CPP_PORT}:8000"
environment:
- NVIDIA_VISIBLE_DEVICES=${FISH_CPP_GPU_DEVICES:-1}
# Default nvidia-container-toolkit only mounts compute libs.
# Vulkan needs the graphics ICD too (libGLX_nvidia, vulkan ICD
# JSON). Without this, Vulkan init in the container fails with
# "no Vulkan ICD" even though the GPU is present.
- NVIDIA_DRIVER_CAPABILITIES=compute,utility,graphics
- FISH_CPP_MODEL=${FISH_CPP_MODEL:-s2-pro-q6_k.gguf}
- FISH_CPP_TOKENIZER=tokenizer.json
- FISH_CPP_DEVICE=0
# Backend selection for the s2 server in entrypoint.sh:
# cuda — -c <id>; alpha CUDA path, GPU 0% util on fish-speech (broken)
# vulkan — -v <id>; README's canonical example, more battle-tested
- FISH_CPP_BACKEND=${FISH_CPP_BACKEND:-vulkan}
volumes:
- ${FISH_CPP_WEIGHTS_DIR}:/weights:ro
- ${FISH_CPP_REFERENCE_DIR}:/references:ro
+12 -4
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@@ -11,18 +11,26 @@ set -euo pipefail
MODEL_PATH="${WEIGHTS_DIR:-/weights}/${FISH_CPP_MODEL:-s2-pro-q6_k.gguf}"
TOKENIZER_PATH="${WEIGHTS_DIR:-/weights}/${FISH_CPP_TOKENIZER:-tokenizer.json}"
DEVICE="${FISH_CPP_DEVICE:-0}"
BACKEND="${FISH_CPP_BACKEND:-vulkan}"
case "$BACKEND" in
cuda) BACKEND_FLAG=(-c "$DEVICE") ;;
vulkan) BACKEND_FLAG=(-v "$DEVICE") ;;
cpu) BACKEND_FLAG=() ;; # no flag → s2 stays on CPU
*) echo "[entrypoint] unknown FISH_CPP_BACKEND=$BACKEND (use cuda/vulkan/cpu)" >&2; exit 2 ;;
esac
if [ ! -f "$MODEL_PATH" ]; then echo "missing model: $MODEL_PATH" >&2; exit 1; fi
if [ ! -f "$TOKENIZER_PATH" ]; then echo "missing tokenizer: $TOKENIZER_PATH" >&2; exit 1; fi
# Background s2 server. Loads model on GPU once, then accepts
# multipart POSTs on localhost:3030/generate.
echo "[entrypoint] starting s2 server on :3030 with CUDA device $DEVICE"
# Background s2 server. Loads model on GPU once (per backend), then
# accepts multipart POSTs on localhost:3030/generate.
echo "[entrypoint] starting s2 server on :3030 with $BACKEND backend, device $DEVICE"
/usr/local/bin/s2 \
--server -H 127.0.0.1 -P 3030 \
-m "$MODEL_PATH" \
-t "$TOKENIZER_PATH" \
-c "$DEVICE" &
"${BACKEND_FLAG[@]}" &
S2_PID=$!
# Wait for s2 to bind 3030 before starting the shim. Avoids the