2 citations · 4 across the 5 of their papers we have counts for
6 papers
Acceleration of Data Analytics on Heterogeneous Supercloud Systems
Georgios Zacharopoulos, Ilias Bournias, Lukas Cavigelli
Heterogeneous Supercloud systems are transforming data analytics by enabling scalable and efficient task distribution across diverse resources. This paper presents computational mo…
AcceLLM: Accelerating LLM Inference using Redundancy for Load Balancing and Data Locality
Ilias Bournias, Lukas Cavigelli, Georgios Zacharopoulos
Large Language Model (LLM) inference on large-scale systems is expected to dominate future cloud infrastructures. Efficient LLM inference in cloud environments with numerous AI acc…
ReDSEa: Automated Acceleration of Triangular Solver on Supercloud Heterogeneous Systems
Georgios Zacharopoulos, Ilias Bournias, Verner Vlacic +1
When utilized effectively, Supercloud heterogeneous systems have the potential to significantly enhance performance. Our ReDSEa tool-chain automates the mapping, load balancing, sc…
Trireme: Exploring Hierarchical Multi-Level Parallelism for Domain Specific Hardware Acceleration
Georgios Zacharopoulos, Adel Ejjeh, Ying Jing +9
The design of heterogeneous systems that include domain specific accelerators is a challenging and time-consuming process. While taking into account area constraints, designers mus…
A Graph Deep Learning Framework for High-Level Synthesis Design Space Exploration
Lorenzo Ferretti, Andrea Cini, Georgios Zacharopoulos +2
The design of efficient hardware accelerators for high-throughput data-processing applications, e.g., deep neural networks, is a challenging task in computer architecture design. I…
Early DSE and Automatic Generation of Coarse Grained Merged Accelerators
Iulian Brumar, Georgios Zacharopoulos, Yuan Yao +3
Post-Moore's law area-constrained systems rely on accelerators to deliver performance enhancements. Coarse grained accelerators can offer substantial domain acceleration, but manua…