Streaming Task Graph Scheduling for Dataflow Architectures
Offered By: Scalable Parallel Computing Lab, SPCL @ ETH Zurich via YouTube
Course Description
Overview
Explore a cutting-edge approach to scheduling task graphs on dataflow architectures in this 29-minute conference talk from #HPDC 2023. Delve into the concept of canonical task graphs and their application in streaming task graph scheduling for dataflow devices. Learn about steady-state analysis techniques and how they inform the partitioning of task graphs into temporally multiplexed components of spatially executed tasks. Discover the potential benefits of this innovative scheduling method, including increased speedup and improved device utilization compared to traditional approaches. Gain insights into the challenges and opportunities presented by dataflow accelerators in the field of high-performance computing. Follow the presentation's logical progression from introduction to conclusions, covering key topics such as spatial block partitioning, task scheduling, and real-world results on synthetic and realistic workloads.
Syllabus
- Introduction
- Canonical Task Graphs
- Steady State Analysis
- Spatial Block Partitioning and Task Scheduling
- Results
- Conclusions
Taught by
Scalable Parallel Computing Lab, SPCL @ ETH Zurich
Related Courses
Intro to Parallel ProgrammingNvidia via Udacity Introduction to Linear Models and Matrix Algebra
Harvard University via edX Введение в параллельное программирование с использованием OpenMP и MPI
Tomsk State University via Coursera Supercomputing
Partnership for Advanced Computing in Europe via FutureLearn Fundamentals of Parallelism on Intel Architecture
Intel via Coursera