Files
foxhunt/crates/ml-ensemble/build.rs
jgrusewski 0914ad0315 feat(ensemble): GPU-native ensemble reduce kernel, remove CPU fallbacks
- New ensemble_reduce_kernel.cu: fused sigmoid→mean→weighted-sum in
  one kernel, single block, thread-per-model. Pure f32, no bf16.
- build.rs: nvcc compilation without --use_fast_math
- aggregate_logits_gpu: loads cubin, uploads raw f32 buffers, launches
  kernel, reads back single scalar. No GpuTensor/ActivationKernels.
- Removed aggregate_logits_cpu (dead code, GPU-only system)
- ml-explainability: removed unreachable dead code after stub return,
  prefixed unused vars. Zero warnings.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-29 22:35:37 +02:00

123 lines
3.4 KiB
Rust

use std::path::{Path, PathBuf};
use std::process::Command;
fn main() {
println!("cargo:rerun-if-changed=build.rs");
// Only compile CUDA kernels when the cuda feature is enabled
if std::env::var("CARGO_FEATURE_CUDA").is_err() {
return;
}
let out_dir = PathBuf::from(std::env::var("OUT_DIR").unwrap());
let kernel_dir = Path::new("src");
// Detect GPU architecture from env or default to sm_80
let cuda_compute_cap = std::env::var("CUDA_COMPUTE_CAP").unwrap_or_else(|_| "80".to_string());
let arch = format!("sm_{cuda_compute_cap}");
// Check if nvcc is available
let nvcc = match find_nvcc() {
Some(p) => p,
None => {
eprintln!(" warning: nvcc not found, skipping ml-ensemble CUDA kernel precompilation");
eprintln!(" Install CUDA toolkit or set CUDA_HOME for GPU builds");
return;
}
};
// Standalone kernels (plain f32, no common header needed)
let kernels = ["ensemble_reduce_kernel.cu"];
let mut failed: Vec<&str> = Vec::new();
for kernel_name in &kernels {
if !try_compile_kernel(&nvcc, kernel_dir, kernel_name, &arch, &out_dir) {
failed.push(kernel_name);
}
}
let passed = kernels.len() - failed.len();
eprintln!(
" ml-ensemble: Precompiled {passed}/{} CUDA kernels ({arch})",
kernels.len()
);
if !failed.is_empty() {
eprintln!(" FAILED: {}", failed.join(", "));
panic!(
"nvcc failed to compile {} ml-ensemble kernel(s): {}",
failed.len(),
failed.join(", ")
);
}
}
/// Compile a single .cu kernel file to a .cubin via nvcc.
fn try_compile_kernel(
nvcc: &Path,
kernel_dir: &Path,
kernel_name: &str,
arch: &str,
out_dir: &Path,
) -> bool {
let kernel_path = kernel_dir.join(kernel_name);
let cubin_name = kernel_name.replace(".cu", ".cubin");
let cubin_path = out_dir.join(&cubin_name);
println!("cargo:rerun-if-changed={}", kernel_path.display());
let status = Command::new(nvcc)
.args([
"-cubin",
&format!("-arch={arch}"),
"-O3",
"--ftz=true",
"--fmad=true",
"--prec-div=true",
"--prec-sqrt=true",
"-o",
cubin_path.to_str().unwrap(),
kernel_path.to_str().unwrap(),
])
.status();
match status {
Ok(s) if s.success() => {
eprintln!(" Compiled {kernel_name} -> {cubin_name} ({arch})");
true
}
Ok(s) => {
eprintln!(
" FAILED: {kernel_name} (exit={})",
s.code().unwrap_or(-1)
);
false
}
Err(e) => {
eprintln!(" FAILED: {kernel_name} (nvcc error: {e})");
false
}
}
}
/// Find nvcc: prefer $CUDA_HOME/bin/nvcc, then check PATH
fn find_nvcc() -> Option<PathBuf> {
if let Ok(home) = std::env::var("CUDA_HOME") {
let nvcc = PathBuf::from(home).join("bin/nvcc");
if nvcc.exists() {
return Some(nvcc);
}
}
for path in &["/usr/local/cuda/bin/nvcc", "/usr/bin/nvcc"] {
let p = PathBuf::from(path);
if p.exists() {
return Some(p);
}
}
match Command::new("nvcc").arg("--version").output() {
Ok(output) if output.status.success() => Some(PathBuf::from("nvcc")),
_ => None,
}
}