KAUST · · Notable
KAUST held its second hackathon and third NVIDIA workshop. Attendees listened to lectures from international experts. Participants worked on porting their scientific applications to a GPU accelerator. Why it matters: Such events help build regional expertise in accelerated computing and attract international collaboration.
KAUST · NVIDIA · hackathon · GPU · accelerator
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arXiv ·
This paper introduces ProgramFC, a fact-checking model that decomposes complex claims into simpler sub-tasks using a library of functions. The model uses LLMs to generate reasoning programs and executes them by delegating sub-tasks, enhancing explainability and data efficiency. Experiments on fact-checking datasets demonstrate ProgramFC's superior performance compared to baseline methods, with publicly available code and data.
MBZUAI ·
A presentation discusses using programmable network devices to reduce communication bottlenecks in distributed deep learning. It explores in-network aggregation and data processing to lower memory needs and increase bandwidth usage. The talk also covers gradient compression and the potential role of programmable NICs. Why it matters: Optimizing distributed deep learning infrastructure is critical for scaling AI model training in resource-constrained environments.
MBZUAI ·
Ang Chen from the University of Michigan presented a talk at MBZUAI on reducing cloud manageability burdens. The talk covered detecting semantic errors before cloud deployment and curating datasets for automated generation of cloud management programs. He introduced the concept of "cloudless computing" to free tenants from cloud management tasks. Why it matters: This research direction could simplify cloud infrastructure management for businesses in the UAE and beyond, allowing them to focus on core activities.
MBZUAI ·
Holger Pirk from Imperial College London is developing a novel approach to data management system composition called BOSS. The system uses a homoiconic representation of data and code and partial evaluation of queries by components, drawing inspiration from compiler-construction research. BOSS achieves a fully composable design that effectively combines different data models, hardware platforms, and processing engines, enabling features like GPU acceleration and generative data cleaning with minimal overhead. Why it matters: This research on composable database systems can broaden the applicability of data management techniques in the GCC region, enabling more flexible and efficient data processing for various applications.