8 papers
CIMinus: Empowering Sparse DNN Workloads Modeling and Exploration on SRAM-based CIM Architectures
Yingjie Qi, Jianlei Yang, Rubing Yang +5
Compute-in-memory (CIM) has emerged as a pivotal direction for accelerating workloads in the field of machine learning, such as Deep Neural Networks (DNNs). However, the effective…
MIREDO: MIP-Driven Resource-Efficient Dataflow Optimization for Computing-in-Memory Accelerator
Xiaolin He, Cenlin Duan, Yingjie Qi +2
Computing-in-Memory (CIM) architectures have emerged as a promising solution for accelerating Deep Neural Networks (DNNs) by mitigating data movement bottlenecks. However, realizin…
HPIM: Heterogeneous Processing-In-Memory-based Accelerator for Large Language Models Inference
Cenlin Duan, Jianlei Yang, Rubing Yang +8
The deployment of large language models (LLMs) presents significant challenges due to their enormous memory footprints, low arithmetic intensity, and stringent latency requirements…
Efficient SRAM-PIM Co-design by Joint Exploration of Value-Level and Bit-Level Sparsity
Cenlin Duan, Jianlei Yang, Yikun Wang +7
Processing-in-memory (PIM) is a transformative architectural paradigm designed to overcome the Von Neumann bottleneck. Among PIM architectures, digital SRAM-PIM emerges as a promis…
CIMFlow: An Integrated Framework for Systematic Design and Evaluation of Digital CIM Architectures
Yingjie Qi, Jianlei Yang, Yiou Wang +6
Digital Compute-in-Memory (CIM) architectures have shown great promise in Deep Neural Network (DNN) acceleration by effectively addressing the "memory wall" bottleneck. However, th…
Prompting Large Language Models for Training-Free Non-Intrusive Load Monitoring
Junyu Xue, Xudong Wang, Xiaoling He +3
Non-intrusive load monitoring (NILM) aims to disaggregate total electricity consumption into individual appliance usage, thus enabling more effective energy management. While deep…
Towards Efficient SRAM-PIM Architecture Design by Exploiting Unstructured Bit-Level Sparsity
Cenlin Duan, Jianlei Yang, Yiou Wang +7
Bit-level sparsity in neural network models harbors immense untapped potential. Eliminating redundant calculations of randomly distributed zero-bits significantly boosts computatio…
DDC-PIM: Efficient Algorithm/Architecture Co-design for Doubling Data Capacity of SRAM-based Processing-In-Memory
Cenlin Duan, Jianlei Yang, Xiaolin He +9
Processing-in-memory (PIM), as a novel computing paradigm, provides significant performance benefits from the aspect of effective data movement reduction. SRAM-based PIM has been d…