42 citations · 202 across the 30 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
RIMMS: Runtime Integrated Memory Management System for Heterogeneous Computing
Serhan Gener, Aditya Ukarande, Shilpa Mysore Srinivasa Murthy +5
Efficient memory management in heterogeneous systems is increasingly challenging due to diverse compute architectures (e.g., CPU, GPU, FPGA) and dynamic task mappings not known at…
Designing High-Performance and Thermally Feasible Multi-Chiplet Architectures enabled by Non-bendable Glass Interposer
Harsh Sharma, Janardhan Rao Doppa, Umit Y. Ogras +1
Multi-chiplet architectures enabled by glass interposer offer superior electrical performance, enable higher bus widths due to reduced crosstalk, and have lower capacitance in the…