NVIDIA / nccl
Optimized primitives for collective multi-GPU communication
NVIDIA / nccl
wilicc / gpu-burn
Multi-GPU CUDA stress test
robertvoy / ComfyUI-Distributed
ComfyUI extension that enables multi-GPU processing locally, remotely and in the cloud
DominikBucko / qwen38-flash-next-2x3090
Qwen3.8-Flash-Next on 2× RTX 3090: with 128 GB RAM up to 4,191 tok/s prefill · 111.5 tok/s decode (131K prompt), full 256K window at 2,865 tok/s; with 64 GB RAM 3,410 tok/s prefill · 84 tok/s decode. New: opt-in uncensored mode (runtime abliteration, no new weights).
RH-RunningHub / MiniMax-H3-MultiGPU-Lightning
MiniMax-H3 multi-GPU inference acceleration: ~12x on 8x RTX 6000D (step distillation + SageAttention2 + Cache-DiT + torch.compile, TP2+Ulysses4 on sglang)
legritos / tfbert-xla-multigpu
TensorFlow 1.x BERT Training with Multi-GPU Gradient Accumulation XLA Mixed Precision 2026
1115714829 / llama.cpp-v100
llama.cpp optimized for NVIDIA Tesla V100 (SM70): large MoE Qwen3.8-Flash-Next with MTP (prefill 3464 tok/s at 200K context, 6x V100-16GB) and Qwen3.8-27B with DFlash2 (decode up to 225 tok/s); 2-6 GPUs, 262K-512K context, multimodal, concurrent serving.
buqi-code / buqi-minimax-h3-multigpu
MiniMax-H3 multi-GPU parallel inference for ComfyUI | 多卡并行加速节点:2-8 GPU Ulysses sequence parallel, bit-identical video+audio generation
dg1kjd / sglang-sxm2
Agentic-coding oriented inference engine for N x V100-SXM2, based on SGLang: GLM-5.3-Flash, Qwen3.8-Flash-Next, DeepSeek-V4.1-Flash, MiniMax-H3.