SambaNova at SC23

Tutorial: Programming Novel AI Accelerators for Scientific Computing

Join a panel of experts, including SambaNova’s own Petro Junior Milan, as they explore the landscape of AI technologies and how you can use them to scale your own AI implementations. In this tutorial, we will present an overview of novel AI accelerators. This includes presentations on hardware and software features on each system. We present steps on how to program these systems by porting deep learning models in standard DL framework implementations, compiling and running on the accelerator hardware.

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Workshop: RDARuntime: An OS for AI Accelerators

Today’s supercomputers are more heterogeneous than ever before. As the share of AI workloads in data centers continues to grow, the share of GPUs and AI-specific hardware grows with it. AI accelerators are different from traditional hardware, affecting all aspects of system design, from data-center scale to single-chip scale. AI accelerators are much more efficient than CPUs or GPUs for some HPC workloads, especially in AI for Science. They also add complexity to system architecture, management, and programming. Although runtime frameworks are critical to reducing system complexity, there is little literature describing AI accelerator runtimes. In this paper, we introduce RDARuntime – an AI-specific OS tailored for the development and operation of SambaNova’s reconfigurable dataflow architecture. We introduce the architecture, our design decisions, and some of the results we have achieved, along with some lessons we have learned while helping to deploy the Reconfigurable Dataflow Unit (RDU) to production environments.

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