Show & Tell 57.2: SparseExpertLayer — Conditional Computation & Expert Parallelism

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SparseExpertLayer Implementation Showcase

Share your implementations of sparse expert computation layers:

Topics

• Expert Architectures: FFN, GLU, SwiGLU (Mixtral), GEGLU expert designs
• Token Dispatch: Efficient all-to-all communication for expert parallelism
• Shared Experts: DeepSeekMoE-style always-active shared expert layers
• Expert Specialization: Measuring and encouraging distinct expert competencies
• Parallel Strategies: Expert parallelism, data parallelism, hybrid approaches
• Memory Optimization: Expert offloading, gradient checkpointing for MoE layers

Key Benchmarks

• Expert computation throughput vs dense equivalent
• All-to-all communication overhead
• Memory footprint per expert
• Expert specialization metrics

Share implementations, performance profiles, and scaling results!

Related: #1083