CBLAS & LAPACKE C API reference skill - Complete documentation for 1284 functions covering numerical linear algebra
Plugin blas_lapack from marketplace datathings in datathings/marketplace. Commands read from the repo's manifest — 17 days ago.
blas_lapackComplete CBLAS and LAPACKE C API reference (LAPACK v3.12.1) covering 1284 functions for numerical linear algebra: BLAS Level 1/2/3 vector and matrix operations, linear system solvers (LU, Cholesky, LDL), eigenvalue/eigenvector computation, singular value decomposition, least squares, QR/LQ factoriza
Comprehensive GreyCat development skill and LSP for graph-based language with built-in persistence. Covers data modeling, API development, parallel processing, frontend integration, and all standard libraries.
1 skill · 8 commands · LSP
NVIDIA CUDA C/C++ skill - Runtime API, cuBLAS, cuFFT, cuSPARSE, cuRAND, cuSolver, Thrust, and Cooperative Groups for GPU-accelerated computing
1 skill
ggml v0.15.1 C tensor library skill - 650+ functions and 98 ops for graph computation, GGUF model I/O, multi-backend inference, GLU activations, SSM/RWKV ops, and ML training
1 skill
GreyCat C API & Standard Library skill - Native C SDK documentation for GreyCat
1 skill
llama.cpp C API reference skill - Complete documentation for 163 functions covering local LLM inference
1 skill
Ollama REST API skill - run and manage local LLMs with chat, generate, embeddings, and custom model creation
1 skill
Repo-aware coding agent harness for kimi-k3-in-c — Kimi K3 (2.78T-param) inference in portable C99: one CPU, 8 GB RAM, no BLAS, no framework, no GPU
2 skills
Math and Science Programming: numerical and scientific computing for software engineers — floating-point arithmetic and the errors it causes, conditioning and stability, the BLAS/LAPACK substrate everything stands on, the tool landscape (MATLAB, Python's scientific stack, Julia, R, Fortran, Mathematica) and how to choose, symbolic versus numeric computation, linear systems, ODEs and PDEs, optimization, statistics and uncertainty, high-performance and GPU computing, and the verification, validation and reproducibility practices that separate trustworthy scientific software from plausible-looking output.
5 skills
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