A toolkit for discovering cluster network topology.

Tartan: Evaluating Modern GPU Interconnect via a Multi-GPU Benchmark Suite

NUMA-aware multi-CPU multi-GPU data transfer benchmarks

競馬データを閲覧できるソフト「KMY競馬」を開発します

This script collects some informations about NVLink and PCI bus traffic of NVidia GPUs. Results are published as prometheus metrics via a websocket.

Real-time per-link NVLink bandwidth monitor + inter-GPU P2P benchmark for NVIDIA multi-GPU systems. Lightweight C++ — the monitor needs no CUDA toolkit.

Ares: Multi-Cluster Kubernetes Scheduler with GPU Topology Optimization (Intra-Node, Inter-Node, Inter-Cluster) and Exactly-Once Execution Semantics

Communication cost modeling for tensor parallel LLM inference with TP vs PP vs hybrid comparison, VRAM analysis, pipeline bubble modeling, regime detection, and cost-efficiency. Shows TP dominates on NVLink, PP has 47% bubble at 8 GPUs, and LLaMA-70B needs 8× A100 or 2× H100 for VRAM.

From-scratch Ring-AllReduce on CPU (C++20) and GPU (CUDA, multi-device): real multi-GPU benchmarks, Nsight profiling, and a bandwidth-optimal ring implementation built without NCCL.

GPU-native agent-swarm orchestration for the NVIDIA AI stack — NeMo, NIM, Triton, DCGM, NGC, NIXL, OpenShell. Spawn GPU-pinned agent teams across DGX/HGX nodes with NVLink-aware scheduling, task DAGs, adaptive scheduling, and full observability.

Close-to-metal C/CUDA lab for RL inference fast paths: persistent GPU workers, hugepage KV arenas, cacheline-aware command rings, and async reward handoff. Goal: remove page faults, malloc/free, scheduler wakeups, CPU round-trips, and KV migration from the per-token path.

C++ command-line tool for managing NVIDIA Fabric Manager partitions. Supports non-interactive mode and advanced partition operations.

Open hardware desktop AI node: 4× Tesla V100, 128GB HBM2, PCIe/NVLink topology and V-Core liquid/air cooling.

A hybrid testbed for evaluating top open-source LLMs (like gpt-oss-20b and Llama 3.3) on local, cloud GPUs, and AWS Inferentia2/Trainium instances, focusing on vLLM optimization, capacity management, kernel bypass, hardware-software co-design, as well as supporting infrastructure such as NCCL, RDMA, NVMeoF.

Technical note + runnable demo: cudaMemcpyPeerAsync isn't capturable into a CUDA graph; capture a peer-to-peer copy as a DeviceToDevice UVA memcpy or a peer-access kernel. Confirmed identical on WSL2 and native Linux.

V-AXION-512: Dual-Tier Post-Entropic Framework. I. PROTOCOL: SR-512, GS-512 & G-STORM-512 for O(1) deterministic state recovery. II. ECOSYSTEM: NEPTUNE-PHX, PHX-BUSLINK, KALMAN-ANCHOR, PHX-GENESIS, DIRECT-FABRIC & AETERNA-FLUX for Sigma-H energy harvesting. — Juho Artturi Hemminki (2026)

NCCL collective benchmarks on an 8×H100 NVSwitch host — busbw vs link budget, NVLS/Ring/Tree, small-message latency floors (eager vs CUDA Graph vs symmetric memory), and the TP-decode comms ceiling they imply. Includes a quiet-box rerun methodology for attribution.

CORTEX - Hardware-Aware AI Workload Scheduler

Comprehensive NCA-AIIO exam prep: study notes, diagrams, screenshots, and field experience for the NVIDIA Certified Associate: AI Infrastructure and Operations certification.