Modern GPU workloads use batching, asynchronous execution, kernel overlap, and GPU sharing to improve utilization, but these optimizations make kernel-level slowdown hard to diagnose. A target kernel may be blocked by extra synchronization or helper kernels, or slowed by concurrent kernels after it starts. Existing tools provide GPU visibility, but they either remain too heavy for continuous online use or focus on coarse-grained symptoms, leaving fine-grained kernel-level root causes to manual analysis. This poster presents Weaver, a low-overhead cross-layer diagnosis framework for GPU kernels. Weaver builds a semantic execution graph from operator, kernel timeline, and warp/block evidence, distinguishes blocked and slowed kernels, and reports an interpretable root-cause chain. Our prototype evaluation shows that Weaver continuously collects runtime evidence with low overhead and accurately localizes anomalies.
This paper presents a tutorial-style, collective-centric taxonomy for collective communication, which organizes recent advances into three layers: communication planning, which generates topology-aware collective schedules; communication execution and adaptation, which maps these schedules onto GPU runtimes and hardware in real clusters; and computation-communication coordination, which turns collective optimization into end-to-end training and inference benefits.
Xuebin Song, Menghao Zhang, Yue Liu et al.· IEEE Network· 0 citations
HyLink is introduced, a two-layer collective communication framework, including a PCIe CCL module and a Multipath Orchestrator module that provides a CPU-driven Domain-Specific Language (DSL) for multi-stage data flows and an auto-pipelined transfer engine for host-side routing and SIMD-accelerated reduction.
Yue Liu, Menghao Zhang, Xuebin Song et al.· Asia-Pacific Workshop on Net...· 0 citations