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SparseLab–real sparse training(CSR+custom kernel) in PyTorch, CPU-first
Custom CPU kernels for sparse training when everyone else chases GPU.
Niche GemBig Brain
DARSHANFOFADIYA
111mo ago
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metal collective communication library (pytorch DDP)
7 starsC++
MCCL Distributed PyTorch training across MacBooks via Thunderbolt
by sassoshots44·Mar 21, 2026·1 point·0 comments
AI Analysis
●●SolidWizardryNiche GemShip It
Two MacBooks syncing gradients over Thunderbolt — slower than single-GPU but it works.
Strengths
- •Fills genuine gap: PyTorch MPS multi-process collectives didn't exist before this.
- •Honest benchmarks admit 10x slower — rare transparency in ML infrastructure projects.
- •Uses vDSP reductions and Metal for fp16/bf16 with overlapped TCP transport.
Weaknesses
- •Only tested on 2 nodes — no validation for larger clusters or production workloads.
- •Performance is worse than single-GPU, limiting real-world utility.
Category
Target Audience
ML researchers with multiple Macs experimenting with distributed training
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NCCL · Gloo · PyTorch Distributed
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