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cs.AR2026
At-the-Roofline Sparse Tensor Contractions on Vector Processors for Transformer Inference
Bowen Wang, Chi Zhang, Diyou Shen +3
Fine-grained weight pruning and activation sparsification have emerged as effective approaches for reducing the compute and memory cost of inference for Transformer models. In the…
cs.AR2026
Accelerating Precise End-to-End Simulation: Latency-Sensitive Many-core System Modeling
Yinrong Li, Zexin Fu, Yichao Zhang +5
Modern large language model workloads put increasing demands on parallel compute capability and on-chip memory capacity, while also stressing fine-grained data movement and synchro…
cs.AR2025
A Dynamic Allocation Scheme for Adaptive Shared-Memory Mapping on Kilo-core RV Clusters for Attention-Based Model Deployment
Bowen Wang, Marco Bertuletti, Yichao Zhang +2
Attention-based models demand flexible hardware to manage diverse kernels with varying arithmetic intensities and memory access patterns. Large clusters with shared L1 memory, a co…