2 citations · 2 across the 6 of their papers we have counts for
5 papers · 1 filter
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…
TensorPool: A 3D-Stacked 8.4TFLOPS/4.3W Many-Core Domain-Specific Processor for AI-Native Radio Access Networks
Marco Bertuletti, Yichao Zhang, Diyou Shen +3
The upcoming integration of AI in the physical layer (PHY) of 6G radio access networks (RAN) will enable a higher quality of service in challenging transmission scenarios. However,…
TROOP: At-the-Roofline Performance for Vector Processors on Low Operational Intensity Workloads
Navaneeth Kunhi Purayil, Diyou Shen, Matteo Perotti +1
The fast evolution of Machine Learning (ML) models requires flexible and efficient hardware solutions as hardwired accelerators face rapid obsolescence. Vector processors are fully…
MemPool Flavors: Between Versatility and Specialization in a RISC-V Manycore Cluster
Sergio Mazzola, Yichao Zhang, Marco Bertuletti +2
As computational paradigms evolve, applications such as attention-based models, wireless telecommunications, and computer vision impose increasingly challenging requirements on com…
TCDM Burst Access: Breaking the Bandwidth Barrier in Shared-L1 RVV Clusters Beyond 1000 FPUs
Diyou Shen, Yichao Zhang, Marco Bertuletti +1
As computing demand and memory footprint of deep learning applications accelerate, clusters of cores sharing local (L1) multi-banked memory are widely used as key building blocks i…