During the PDS/HPDA Seminar of 2/12/2022 from 10:00 to 10:50, Aleksandar Maksimovic will present a reading group talk and Etienne Deveaux will present a reading group talk.
# Reading group: Helios: Heterogeneous Multiprocessing with Satellite Kernels (SOSP’09)\n\nPresented by Aleksandar Maksimovic on 2/12/2022 at 10:00. Attending this presentation is mandatory for the master students.
Helios is an operating system designed to simplify the task of writing, deploying, and tuning applications for heterogeneous platforms. Helios introduces satellite kernels, which export a single, uniform set of OS abstractions across CPUs of disparate architectures and performance characteristics. Access to I/O services such as file systems are made transparent via remote message passing, which extends a standard microkernel message-passing abstraction to a satellite kernel infrastructure. Helios retargets applications to available ISAs by compiling from an intermediate language. To simplify deploying and tuning application performance, Helios exposes an affinity metric to developers. Affinity provides a hint to the operating system about whether a process would benefit from executing on the same platform as a service it depends upon. We developed satellite kernels for an XScale programmable I/O card and for cache-coherent NUMA architectures. We offloaded several applications and operating system components, often by changing only a single line of metadata. We show up to a 28% performance improvement by offloading tasks to the XScale I/O card. On a mail-server benchmark, we show a 39% improvement in performance by automatically splitting the application among multiple NUMA domains.
# Reading group: StarPU: A Unified Platform for Task Scheduling on Heterogeneous Multicore Architectures (EuroPar’09)\n\nPresented by Etienne Deveaux on 2/12/2022 at 10:30. Attending this presentation is mandatory for the master students.
In the field of HPC, the current hardware trend is to design multiprocessor architectures that feature heterogeneous technologies such as specialized coprocessors (e.g., Cell/BE SPUs) or data-parallel accelerators (e.g., GPGPUs). Approaching the theoretical performance of these architectures is a complex issue. Indeed, substantial efforts have already been devoted to efficiently offload parts of the computations. However, designing an execution model that unifies all computing units and associated embedded memory remains a main challenge. We have thus designed STAR PU, an original runtime system providing a high-level, unified execution model tightly coupled with an expressive data management library. The main goal of S TARPU is to provide numerical kernel designers with a convenient way to generate parallel tasks over heterogeneous hardware on the one hand, and easily develop and tune powerful scheduling algorithms on the other hand. We have developed several strategies that can be selected seamlessly at run time, and we have demonstrated their efficiency by analyzing the impact of those scheduling policies on several classical linear algebra algorithms that take advantage of multiple cores and GPUs at the same time. In addition to substantial improvements regarding execution times, we obtained consistent superlinear parallelism by actually exploiting the heterogeneous nature of the machine.
See you soon,
The PDS/HPDA Seminar organizing committee