Sim-FA is a new simulator that instruments FlashAttention-3 for cycle-accurate GPGPU analysis, achieving 5.7% average error on H800 while explaining inaccuracies in existing DRAM traffic models.
FLAT: An optimized dataflow for mitigating attention bot- tlenecks
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Mambalaya delivers 4.9x prefill and 1.9x generation speedups on Mamba layers over prior accelerators by systematically fusing inter-Einsum operations.
FILCO introduces a real-time reconfigurable composing architecture for DNN acceleration that achieves 1.3x-5x better throughput and hardware efficiency than prior designs on diverse workloads via an analytical model and two-stage design space exploration.
citing papers explorer
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Sim-FA: A GPGPU Simulator Framework for Fine-Grained FlashAttention Pipeline Analysis
Sim-FA is a new simulator that instruments FlashAttention-3 for cycle-accurate GPGPU analysis, achieving 5.7% average error on H800 while explaining inaccuracies in existing DRAM traffic models.
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Mambalaya: Einsum-Based Fusion Optimizations on State-Space Models
Mambalaya delivers 4.9x prefill and 1.9x generation speedups on Mamba layers over prior accelerators by systematically fusing inter-Einsum operations.
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FILCO: Flexible Composing Architecture with Real-Time Reconfigurability for DNN Acceleration
FILCO introduces a real-time reconfigurable composing architecture for DNN acceleration that achieves 1.3x-5x better throughput and hardware efficiency than prior designs on diverse workloads via an analytical model and two-stage design space exploration.