4 papers
Reducing the GPU Memory Bottleneck with Lossless Compression for ML -- Extended
Aditya K Kamath, Arvind Krishnamurthy, Marco Canini +1
Machine learning (ML) training and inference often process data sets far exceeding GPU memory capacity, forcing them to rely on PCIe for on-demand tensor transfers, causing critica…
Nonparametric Teaching of Attention Learners
Chen Zhang, Jianghui Wang, Bingyang Cheng +7
Attention learners, neural networks built on the attention mechanism, e.g., transformers, excel at learning the implicit relationships that relate sequences to their corresponding…
Efficient and Adaptable Detection of Malicious LLM Prompts via Bootstrap Aggregation
Shayan Ali Hassan, Tao Ni, Zafar Ayyub Qazi +1
Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language understanding, reasoning, and generation. However, these systems remain susceptible to ma…
Cloud abstractions for AI workloads
Marco Canini, Theophilus A. Benson, Ricardo Bianchini +4
AI workloads, often hosted in multi-tenant cloud environments, require vast computational resources but suffer inefficiencies due to limited tenant-provider coordination. Tenants l…