Callisto

The Callisto project investigates how systems software can evolve to better support parallel and distributed runtime systems on tightly-coupled clusters and on large NUMA systems.

Project Details

Callisto

Callisto

The Callisto project investigates how systems software can evolve to better support parallel and distributed runtime systems on tightly-coupled clusters and on large NUMA systems.

Project Overview

Modern h/w and s/w looks radically different to the HPC and server workloads which have traditionally motivated parallel programming: Individual machines are internally more complex with multiple processor types, NUMA domains and hot-swap components. Workload resource demands are also more complex, with bursty behavior over short timescales, and an ability to elastically use more/fewer resources as they are available. Furthermore, the need to consolidate workloads on large machines or clusters brings a renewed need to handle resource management on behalf of multiple jobs and multiple users.

In Callisto, we are looking at how to re-architect the interaction between virtualization, distribution, and parallel runtime systems in order to better support these new workloads.

A particular focus is the needs of parallel and distributed graph analytics workloads (such as those generated by the Green-Marl DSL) when deployed on large NUMA systems, or on clusters of machines connected by a low-latency interconnect.

Principal Investigator

Sungpack Hong

Director, Research And Advanced Development

Sungpack Hong is a Principal Member of Technical Staff for Oracle Labs.

Education:

* PhD EE, 2012 (expected), Stanford University

* MS EE&CS, 2001, KAIST, South Korea

* BS Computer Science, 1999, KAIST, South Korea

Publications