2026-08-13 –, Room 3
Stencil operations are a cornerstone in many fields, including fluid and gas flow simulations, machine learning/AI, computer graphics, image processing, and many more. Stencil operations (also known as windowed operations) allow a normal elementwise operation to additionally access neighboring elements, instead of just the currently-selected element. The are a number of stencil computation libraries in Julia, such as ImageFiltering.jl, ParallelStencil.jl, Stencils.jl, and now Dagger.jl (the focus of this talk). Dagger in particular makes it easy to define stencil operations that run across multiple CPUs, multiple GPUs, and across multiple nodes, and supports many kinds of boundary conditions, arbitrary numbers of dimensions, and flexible neighborhood sizing. We will discuss and compare the differences between the various stencil libraries, and see how easy it is to write parallel stencils in each library. We will also look at Dagger’s stencil performance in a variety of microbenchmarks.
Julian is a Research Software Engineer at MIT's JuliaLab, where he focuses on improving Julia's support for HPC and GPU computing. Julian has previously authored and maintained the AMDGPU.jl package (for programming AMD's GPUs from Julia), and now focuses his efforts on maintaining and developing the Dagger.jl package, to improve the state of productive parallel programming.
Consultant at MIT's JuliaLab, Co-maintainer of Dagger. My interests span from more broad topics such as the accessibility and educational initiatives for parallel computing to Applied Physics and Numerical Linear Algebra.
Rabab Alomairy is a postdoc in the Julia Lab located in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT). Rabab's research is centered around task-based numerical libraries and applications, performance optimizations for multicore/manycore architectures and hardware accelerators, dynamic runtime systems, GPU programming, and machine learning and artificial intelligence.