3 papers
cs.AR2025
CHIPSIM: A Co-Simulation Framework for Deep Learning on Chiplet-Based Systems
Lukas Pfromm, Alish Kanani, Harsh Sharma +3
Due to reduced manufacturing yields, traditional monolithic chips cannot keep up with the compute, memory, and communication demands of data-intensive applications, such as rapidly…
cs.AR2025
THERMOS: Thermally-Aware Multi-Objective Scheduling of AI Workloads on Heterogeneous Multi-Chiplet PIM Architectures
Alish Kanani, Lukas Pfromm, Harsh Sharma +3
Chiplet-based integration enables large-scale systems that combine diverse technologies, enabling higher yield, lower costs, and scalability, making them well-suited to AI workload…
cs.LG2025
eMamba: Efficient Acceleration Framework for Mamba Models in Edge Computing
Jiyong Kim, Jaeho Lee, Jiahao Lin +4
State Space Model (SSM)-based machine learning architectures have recently gained significant attention for processing sequential data. Mamba, a recent sequence-to-sequence SSM, of…