Every program artifact: a benchmark or application described once and compiled and run on any compute target (cpu, cuda, ...) by cx program run <name> <target>, the tools it needs set up on the way.
The commands:
cx program listcx program run <name> cpucx program run <name> cudacx repo get cTuningLabs@cmeta-aops) and every row below is a command on your machine.
The category itself - its commands and API - is here.
| Artifact | Comes from | What it is for | Tags |
|---|---|---|---|
| build-llama-cpp | (cTuningLabs@cmeta-aops) | Build llama.cpp from source for the selected compute target and run it on a GGUF model with a prompt dataset. | |
| build-pytorch | (cTuningLabs@cmeta-aops) | Build PyTorch from source through the program pipeline (Python, compilers, CMake) for the selected target. | |
| build-pytorchvision | (cTuningLabs@cmeta-aops) | Build torchvision from source against a locally built PyTorch. | |
| build-torch-cpp | (cTuningLabs@cmeta-aops) | Build LibTorch, the PyTorch C++ distribution, from source with CMake and Ninja. | |
| cbench-automotive-susan | (cTuningLabs@cmeta-aops) | cBench automotive susan image-processing benchmark (edges, corners, smoothing) on a PGM image dataset; runs on CPU and Android. | |
| image-classification-onnx | (cTuningLabs@cmeta-aops) | Image classification with ONNX Runtime in Python on CPU, CUDA or XPU, with optional profiling. | |
| image-classification-pytorch | (cTuningLabs@cmeta-aops) | Image classification with a pretrained PyTorch model in Python on the selected target. | |
| lib-milepost | (cTuningLabs@cmeta-aops) | Build the MILEPOST codelet support library used by the MILEPOST benchmarks. | |
| lib-polybench | (cTuningLabs@cmeta-aops) | Build the PolyBench support library used by the PolyBench kernels. | |
| lib-xopenme | (cTuningLabs@cmeta-aops) | Build the xOpenME instrumentation library that records run-time statistics of benchmarks. | |
| llama-cpp | (cTuningLabs@cmeta-aops) | Run a GGUF language model with a prebuilt or cached llama.cpp on a prompt dataset. | |
| milepost-codelet-mibench-automotive-susan-e-src-susan-codelet-10-1 | (cTuningLabs@cmeta-aops) | A MILEPOST codelet extracted from MiBench susan edges (loop 10-1): a small kernel for compiler and hardware studies, on CPU and Android. | |
| model-cnn-ylecun-mnist-pytorch | (cTuningLabs@cmeta-aops) | Train and run LeCun's CNN on MNIST with PyTorch on CPU or CUDA, with optional profiling. | |
| polybench-cpu-gemm | (cTuningLabs@cmeta-aops) | PolyBench GEMM kernel (dense matrix multiplication) on CPU. | |
| polybench-gemm-cpu-cuda | (cTuningLabs@cmeta-aops) | PolyBench GEMM kernel on CPU or CUDA with a configurable matrix size. | |
| template-c-cpu | (cTuningLabs@cmeta-aops) | The base recipe every program inherits: select the target and compiler, compile the sources, run with datasets and models, collect outputs. | |
| test-hello-c-cpu | (cTuningLabs@cmeta-aops) | Minimal hello-world C program that writes a statistics file; the smallest end-to-end check of the program pipeline. | |
| test-nmm-c-cpu | (cTuningLabs@cmeta-aops) | Native matrix multiplication in C with OpenMP, OpenSSL and math libraries; configurable precision, sizes and repeats. | |
| test-nmm-cpp-cpu | (cTuningLabs@cmeta-aops) | Native matrix multiplication in C++ with OpenMP, OpenSSL and math libraries; configurable precision, sizes and repeats. | |
| test-nmm-go-cpu | (cTuningLabs@cmeta-aops) | Native matrix multiplication in Go; configurable precision, sizes and repeats. | |
| test-nmm-java-cpu | (cTuningLabs@cmeta-aops) | Native matrix multiplication in Java, compiled with javac and run with java. | |
| test-nmm-mojo-cpu | (cTuningLabs@cmeta-aops) | Native matrix multiplication in Mojo on CPU. | |
| test-nmm-nvcc-cuda | (cTuningLabs@cmeta-aops) | Native matrix multiplication in CUDA compiled with nvcc; large default sizes for GPU timing. | |
| test-nmm-objc-metal | (cTuningLabs@cmeta-aops) | Native matrix multiplication in Objective-C with Metal compute on Apple GPUs. | |
| test-nmm-python-cpu | (cTuningLabs@cmeta-aops) | Native matrix multiplication in Python on CPU, with optional profiling. | |
| test-nmm-rust-cpu | (cTuningLabs@cmeta-aops) | Native matrix multiplication in Rust on CPU. | |
| test-nmm-swift-cpu | (cTuningLabs@cmeta-aops) | Native matrix multiplication in Swift on CPU. | |
| test-nmm-torch-cpp | (cTuningLabs@cmeta-aops) | Matrix multiplication in C++ against LibTorch, the PyTorch C++ API. | |
| test-pytorch-with-audio | (cTuningLabs@cmeta-aops) | Check PyTorch with torchaudio in Python on the selected target, with optional profiling. | |
| test-pytorch-with-vision | (cTuningLabs@cmeta-aops) | Check PyTorch with torchvision in Python on the selected target (a C compiler is set up for extensions). | |
| test-vllm | (cTuningLabs@cmeta-aops) | Start vLLM from Python on CPU or CUDA with a pinned or default version, with optional profiling. |
Nothing matches that filter.
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