Tags · #gpu

Ai2 Replaces Priority Scheduling with GPU Time Budgets to Solve Tragedy of the Commons

Read this because This case study demonstrates how economic incentives like time budgets can solve technical scheduling problems like resource squatting and priority inflation in shared GPU clusters.

Ai2 shifts from a flawed priority-based scheduler to a hierarchical fair-share system with GPU time budgets, improving cluster occupancy and research impact.

10 OCT 2 MIN READ Practitioner note gpu scheduling ai-infrastructure resource-allocation

Flash-dLLM: IO-Aware KV Caching and Parallel Decoding for Fast, Memory-Efficient Diffusion LLMs

Read this because Researchers and engineers working with diffusion-based language models can significantly reduce inference latency and memory overhead by adopting this training-free acceleration framework.

Flash-dLLM introduces an I/O-aware fused KV-cache kernel and parallel decoding strategy to accelerate diffusion LLMs without auxiliary models.

23 SEP 2 MIN READ Practitioner note llm diffusion gpu optimization

GPU-CFR: Compiling Game Trees for 80x Faster CFR on GPUs

Read this because This compiler approach eliminates kernel launch overhead, making GPU CFR viable for large-scale games where CPUs previously dominated.

GPU-CFR compiles game trees to static dataflow, achieving up to 80x speedup over prior GPU implementations and beating CPU baselines.

11 SEP 2 MIN READ Practitioner note gpu cfr cuda compiler