45 citations · 62 across the 8 of their papers we have counts for
8 papers
Data Transfer Optimizations for Host-CPU and Accelerators in AXI4MLIR
Jude Haris, Nicolas Bohm Agostini, Antonino Tumeo +2
As custom hardware accelerators become more prevalent, it becomes increasingly important to automatically generate efficient host-driver code that can fully leverage the capabiliti…
AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators
Nicolas Bohm Agostini, Jude Haris, Perry Gibson +6
This paper addresses the need for automatic and efficient generation of host driver code for arbitrary custom AXI-based accelerators targeting linear algebra algorithms, an importa…
GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption
Kaustubh Shivdikar, Yuhui Bao, Rashmi Agrawal +9
Fully Homomorphic Encryption (FHE) enables the processing of encrypted data without decrypting it. FHE has garnered significant attention over the past decade as it supports secure…
Thought Bubbles: A Proxy into Players' Mental Model Development
Omid Mohaddesi, Noah Chicoine, Min Gong +5
Studying mental models has recently received more attention, aiming to understand the cognitive aspects of human-computer interaction. However, there is not enough research on the…
Accelerating Polynomial Multiplication for Homomorphic Encryption on GPUs
Kaustubh Shivdikar, Gilbert Jonatan, Evelio Mora +6
Homomorphic Encryption (HE) enables users to securely outsource both the storage and computation of sensitive data to untrusted servers. Not only does HE offer an attractive soluti…
To Trust or to Stockpile: Modeling Human-Simulation Interaction in Supply Chain Shortages
Omid Mohaddesi, Jacqueline Griffin, Ozlem Ergun +3
Understanding decision-making in dynamic and complex settings is a challenge yet essential for preventing, mitigating, and responding to adverse events (e.g., disasters, financial…
SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference
Jude Haris, Perry Gibson, José Cano +2
Edge computing devices inherently face tight resource constraints, which is especially apparent when deploying Deep Neural Networks (DNN) with high memory and compute demands. FPGA…
Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search
Zheng Zhan, Yifan Gong, Pu Zhao +9
Though recent years have witnessed remarkable progress in single image super-resolution (SISR) tasks with the prosperous development of deep neural networks (DNNs), the deep learni…