SegFold achieves 1.95× geometric-mean speedup over prior SpGEMM accelerators via fine-grained dynamic scheduling and remapping in its Segment dataflow.
Nisa Bostancı, Ataberk Olgun, A
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ORBIS uses output-guided token reduction and DATM to achieve 2x higher token reduction than AsymRnR, with up to 4.5x speedup and 79.3% energy savings versus A100 GPU for video DiT models.
A trace-driven simulator models Hopper TMA/WGMMA pipelines at WarpGroup granularity, matching H800 FlashAttention-3 latency to 5.7% MAPE, and its analytical model explains GenZ's long-sequence DRAM underestimation.
PLENA introduces a co-designed system with three optimization pathways for long-context agentic LLM inference, claiming up to 2.23x throughput over A100 and 4.04x energy efficiency.
citing papers explorer
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SegFold: Accelerating Sparse GEMM with a Fine-Grained Dynamic Dataflow
SegFold achieves 1.95× geometric-mean speedup over prior SpGEMM accelerators via fine-grained dynamic scheduling and remapping in its Segment dataflow.
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ORBIS: Output-Guided Token Reduction with Distribution-Aware Matching for Video Diffusion Acceleration
ORBIS uses output-guided token reduction and DATM to achieve 2x higher token reduction than AsymRnR, with up to 4.5x speedup and 79.3% energy savings versus A100 GPU for video DiT models.
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Sim-FA: A GPGPU Simulator Framework for Fine-Grained Asynchronous Pipeline Analysis
A trace-driven simulator models Hopper TMA/WGMMA pipelines at WarpGroup granularity, matching H800 FlashAttention-3 latency to 5.7% MAPE, and its analytical model explains GenZ's long-sequence DRAM underestimation.
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Combating the Memory Walls: Optimization Pathways for Long-Context Agentic LLM Inference
PLENA introduces a co-designed system with three optimization pathways for long-context agentic LLM inference, claiming up to 2.23x throughput over A100 and 4.04x energy efficiency.