6 papers
TMPDiff: Temporal Mixed-Precision for Diffusion Models
Basile Lewandowski, Simon Kurz, Aditya Shankar +3
Diffusion models are the go-to method for Text-to-Image generation, but their iterative denoising processes has high inference latency. Quantization reduces compute time by using l…
Match & Choose: Model Selection Framework for Fine-tuning Text-to-Image Diffusion Models
Basile Lewandowski, Robert Birke, Lydia Y. Chen
Text-to-image (T2I) models based on diffusion and transformer architectures advance rapidly. They are often pretrained on large corpora, and openly shared on a model platform, such…
Building an Accelerated OpenFOAM Proof-of-Concept Application using Modern C++
Giulio Malenza, Giovanni Stabile, Filippo Spiga +2
The modern trend in High-Performance Computing (HPC) involves the use of accelerators such as Graphics Processing Units (GPUs) alongside Central Processing Units (CPUs) to speed up…
Optimization-Free Universal Watermark Forgery with Regenerative Diffusion Models
Chaoyi Zhu, Zaitang Li, Renyi Yang +4
Watermarking becomes one of the pivotal solutions to trace and verify the origin of synthetic images generated by artificial intelligence models, but it is not free of risks. Recen…
Exploring energy consumption of AI frameworks on a 64-core RV64 Server CPU
Giulio Malenza, Francesco Targa, Adriano Marques Garcia +2
In today's era of rapid technological advancement, artificial intelligence (AI) applications require large-scale, high-performance, and data-intensive computations, leading to sign…
TabuLa: Harnessing Language Models for Tabular Data Synthesis
Zilong Zhao, Robert Birke, Lydia Chen
Tabular data synthesis is crucial for addressing privacy and security concerns in industries reliant on tabular data. While recent advancements adopt large language models (LLMs) f…