34 citations · 113 across the 17 of their papers we have counts for
4 papers · 1 filter
Leveraging Highly Approximated Multipliers in DNN Inference
Georgios Zervakis, Fabio Frustaci, Ourania Spantidi +3
In this work, we present a control variate approximation technique that enables the exploitation of highly approximate multipliers in Deep Neural Network (DNN) accelerators. Our ap…
RankMap: Priority-Aware Multi-DNN Manager for Heterogeneous Embedded Devices
Andreas Karatzas, Dimitrios Stamoulis, Iraklis Anagnostopoulos
Modern edge data centers simultaneously handle multiple Deep Neural Networks (DNNs), leading to significant challenges in workload management. Thus, current management systems must…
LLM-dCache: Improving Tool-Augmented LLMs with GPT-Driven Localized Data Caching
Simranjit Singh, Michael Fore, Andreas Karatzas +6
As Large Language Models (LLMs) broaden their capabilities to manage thousands of API calls, they are confronted with complex data operations across vast datasets with significant…
An LLM-Tool Compiler for Fused Parallel Function Calling
Simranjit Singh, Andreas Karatzas, Michael Fore +2
State-of-the-art sequential reasoning in Large Language Models (LLMs) has expanded the capabilities of Copilots beyond conversational tasks to complex function calling, managing th…