AI & ML
SGL: Towards a Bridging Model for Heterogeneous Hierarchical Platforms
arXiv cs.DC0 views
arXiv:2610.33995v1 Announce Type: new Abstract: This paper introduces the Scatter-Gather parallel-programming and parallel-execution model in the form of a simple imperative Scatter-Gather Language (SGL). Its design is based on past experience with bulk-synchronous parallel (BSP) programming and BSP language design. SGL's novel features are motivated by the last decade's move towards multi-level and heterogeneous parallel architectures involving multi-core processors, graphics accelerators and hierarchical routing networks in the largest multiprocessing systems. The design of SGL is coherent with L. Valiant's Multi-BSP while offering a programming interface that is even simpler than the primitives of Bulk-Synchronous Parallel ML (BSML). SGL appears to cover a large subset of all BSP algorithms while avoiding complex message-passing programming. Like all BSP-inspired systems, it supports predictable, portable and scalable performance. Moreover, SGL's explicit data distribution will allow automatic or programmable load-balancing.
Source:https://arxiv.org/abs/2610.33995PreviousSpeeding up Log-Sum-Exp: Kernel Fusion at the Memory Wall, Integer Arithmetic at the Compute WallNextInferScale: Kubernetes-Native Predictive Autoscaling for SLO-Aware AI Inference
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