Simple Huffman coding
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Updated
Jul 23, 2021 - C++
Simple Huffman coding
A local-first, automated LLM benchmarking tool that runs llama-bench against your GGUF models across CPU & GPU and gives you an interactive comparison dashboard.
Run 35B MoE models on a laptop with only 16 GB of RAM
Offline AI inference engine with C++/CMake core and multi-platform support
Production-grade C++20/CUDA distributed LLM inference system with TCP networking, MPI scheduling, and content-addressed storage. Features comprehensive benchmarking (p50/p95/p99 latencies), epoll async I/O, and optimizations for low-VRAM GPUs (1GB+). 2500+ LOC demonstrating systems engineering expertise.
Asynchronous Inference Primitive.
ONNX Runtime wrapper addon for TrussC
A RESTful API server to perform inference based on Intel OpenVINO 2018 R5
High-perf C++ AI/ML inference engine with ONNX Runtime & LibTorch. CPU default, GPU opt-in. CLI + REST API, cross-platform via CMake/Docker. Auto-fetch models/assets, CUDA runtime check, CI merge gating, future multi-model & GPU training support.
C++17 inference platform: belief propagation, Mamba SSM, MoE, neuro-symbolic logic, SIMD containers
Simulates and compares GPU tensor memory allocation strategies (FreeList, Buddy, Slab, LifetimeAware) for LLM inference. 108-run sweep across 9 strategies, 4 pool sizes, 3 batch sizes. Key finding: simple free-list heuristics beat buddy/slab for continuous tensor size distributions.
Custom CUDA implementation for LLM inference with MPI-based distributed computing. Memory-efficient layer offloading, multi-rank coordination, and GPU optimization for constrained hardware (1GB VRAM).
Pure C++20 vision-model inference (segmentation, depth, normals, pose) on brotensor from HuggingFace safetensors.
Build and test TurboQuant for llama.cpp-style runtimes with benchmarks, integration patches, and long-context validation
Educational C++ handwritten-digit classifier built from scratch with custom matrix, activation, and dense-layer implementations.
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