Event schedule
Exhibition and Conference Center, KKUaa Campus
HPC in the Cloud: Unleash Exascale Power & Future-Proof Your Work
11:00 am - 11:30 am
- Abstract: Methods in Machine and Deep Learning are being investigated to either augment or replace traditional simulation. Contemporary trends in hardware and software have enabled convergence of HPC and AI. In this workshop we survey these trends and explore what is available on system level and in software to ease the transition to developing data science workloads. The talks include a walk through the current hardware and system resources available to accelerate the Data Science workflows. It is followed by the cataloging of software tools and frameworks available to develop ML/DL models, accelerate their training process and handle the associated...
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Unveiling the Power of Supercomputing
9:40 am - 10:20 am
- High-Performance Computing (HPC) has become a cornerstone of innovation across various scientific and industrial domains. This workshop offers a comprehensive introduction to HPC, highlighting its significance in solving complex computational problems that are beyond the reach of standard computing systems. We will explore the critical role HPC plays in advancing research and development, providing an overview of the hardware architectures, software frameworks, and operational strategies that drive modern supercomputing environments. Participants will gain insights into the essential components of HPC clusters and applications, setting the stage for a deeper understanding of this powerful technology
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Harnessing the Power of Parallel Programming with OpenMP
10:50 am - 11:50 am
- Parallel programming is a fundamental skill for leveraging the full potential of modern CPU architectures in High-Performance Computing (HPC). In this workshop, we delve into the basics of OpenMP, a widely adopted parallel programming model that simplifies the development of multi-threaded applications. Participants will learn about the importance of parallelism in HPC and how OpenMP can be utilized to optimize computational workloads. Through practical examples and hands-on sessions on our online platform CrackHPC, we will explore the core concepts of OpenMP, demonstrating its impact on performance and efficiency in real-world HPC applications.
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Hands on workshop on training a DL model in parallel
10:20 am - 11:50 am
Parallel and distributed ML/DL on HPC platforms
9:40 am - 10:10 am
- Training ML and DL models can be a computationally expensive task to perform. If done repeatedly, it can slow down the overall scientific investigation. There exist a range of libraries today which can enable parallelism in training of ML/DL models. In this talk, we present a walkthrough of the life cycle of a typical ML/DL model development and survey the trends and techniques used to accelerating the model pre-training/finetuning on HPC resources.
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Trends in HPC architecture enabling accelerated Data Science
9:00 am - 9:40 am
- KAUST Supercomputing Lab supports a significant group of users using our machines for AI workloads. Based on our experience, we catalogue the current and future trends of hardware that primarily hosts Data Science workloads in present day. We survey the computer architectures designed to accelerate both HPC and ML/DL workloads and the interconnect requirements and available options to scale out these workloads. We also discuss the workload and data management characteristics for AI related workload and available options to run them with fairness in a multi-user environment. We then survey the solutions, either bespoke or turnkey, those are efficiently addressing...
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Deploying Deep learning models on NVIDIA Triton Inference Server
12:50 pm - 1:50 pm
- Deploying AI models can often require advanced setups and custom wrappers, adding extra complexity and time to projects. NVIDIA’s Triton Inference Server simplifies this process by providing a unified, easy-to-use framework for deploying AI models. Triton supports all major backends, including PyTorch, TensorFlow, and TensorRT, and offers an out-of-the-box API endpoint. In this session, we’ll explore how to deploy a pre-trained DL model into Triton in two versions: Pytorch and TensorRT. We’ll also discuss strategies for optimizing resource utilization and demonstrate how Triton can be applied in real-world scenarios.
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Hands-on AI Tools and Techniques
12:50 pm - 2:50 pm
- This workshop is designed to provide an integrated introduction to the realms of Machine Learning (ML) and Deep Learning (DL), two critical subsets of Artificial Intelligence (AI). Without delving into overwhelming technical complexities, attendees will gain a foundational understanding of machine learning and deep learning models. Utilizing the top-tier resources of the KAUST Visualization Core Lab, attendees will experience a mix of indepth lectures and hands-on sessions, ensuring a foundational grasp of the subject. This workshop is ideal for those looking to embark on a journey into AI, as well as for professionals seeking to enhance their knowledge in this...
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