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A Framework for Adaptable Operating and Runtime Systems. Ron Brightwell Scalable Computing Systems Sandia National Laboratories Albuquerque, New Mexico, USA. FAST-OS PI Meeting June 9-10, 2005. Project Details. Sandia National Laboratories Neil Pundit (Project Director)

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a framework for adaptable operating and runtime systems

A Framework for Adaptable Operating and Runtime Systems

Ron Brightwell

Scalable Computing Systems

Sandia National Laboratories

Albuquerque, New Mexico, USA

FAST-OS PI Meeting

June 9-10, 2005

Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company,for the United States Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000.

project details
Project Details
  • Sandia National Laboratories
    • Neil Pundit (Project Director)
    • Ron Brightwell (Coordinating PI)
    • Rolf Riesen, Trammell Hudson, Zaid Adubayeh
  • University of New Mexico
    • Barney Maccabe (PI)
    • Patrick Bridges
  • California Institute of Technology
    • Thomas Sterling (PI)
cluster network hardware
Cluster Network Hardware
  • DMA between NIC and host memory
    • Physical addresses on NIC
    • Can be user- or kernel-space
    • Memory descriptors on NIC
  • Benefits associated with offloading
    • Reduced overhead
    • Increased bandwidth
    • Reduced latency
os bypass versus splintering
OS Bypass Versus Splintering

Cluster Architecture

Distributing little bits

of the OS

other issues
Other Issues
  • General-purpose operating systems
    • Generality comes at the cost of performance for all applications
    • Assume a generic architectural model
      • Difficult to expose novel features
  • Lightweight operating systems
    • Limited functionality
    • Difficult to add new features
    • Designed to be used in the context of a specific usage model
  • Operating system is an impediment to new architectures and programming models
lwk influences
LWK Influences
  • Lightweight OS
    • Small collection of apps
      • Single programming model
    • Single architecture
    • Single usage model
    • Small set of shared services
    • No history
  • Puma/Cougar
    • MPI
    • Distributed memory
    • Space-shared
    • Parallel file system
    • Batch scheduler
current and future system demands
Current and Future System Demands
  • Architecture
    • Modern ultrascale machines have widely varying system-level and node-level architectures
    • Future systems will have further hardware advances (e.g., multi-core chips, PIMs)
  • Programming model
    • MPI, Thread, OpenMP, PGAS, …
  • External services
    • Parallel file systems, dynamic libraries, checkpoint/restart, …
  • Usage model
    • Single, large, long-running simulation
    • Parameter studies with thousands of single-processor, short-running jobs
project goals
Project Goals
  • Realize a new generation of scalable, efficient, reliable, easy to use operating systems for a broad range of future ultrascale high-end computing systems based on both conventional and advanced hardware architectures and in support of diverse, current and emerging parallel programming models.
  • Devise and implement a prototype system that provides a framework for automatically configuring and building lightweight operating and runtime system based on the requirements presented by an application, system usage model, system architecture, and the combined needs for shared services.
  • Define and build a collection of micro-services
    • Small components with well-defined interfaces
    • Implement an indivisible portion of service semantics
    • Fundamental elements of composition and re-use
  • Combine micro-services specifically for an application and a target platform
  • Develop tools to facilitate the synthesis of required micro-services
tools for combining micro services
Tools for Combining Micro-Services
  • Need to insure that required micro-services are available
  • Need to insure that applications are isolated from one another within the context of a given usage model
  • Verifying that a set of constraints are met
  • Further work will allow for reasoning about additional system properties, such as performance based on feedback from previous runs
  • 12 months
    • Define basic framework and micro-service APIs
    • Define initial micro-services for supporting a lightweight kernel equivalent
    • Identify applications and related metrics for evaluating resulting systems
  • 24 months
    • Demonstrate configuration and linking tools with multiple lightweight kernel configurations
    • Define application-specific micro-services for optimizing application performance
    • Define shared-service micro-services for common application services (e.g. TCP/IP)
timetable cont d
Timetable (cont’d)
  • 36 months
    • Demonstrate instance of framework for PIM-based system on base-level PIM architecture simulator
    • Demonstrate application/kernel configurability using application-specific and shared-service micro-services
    • Release complete software package as open source
    • Provide detailed report summarizing completed and future work
related work
Related Work
  • Microkernels
    • K42, L4, Pebble, Mach, …
    • Exo-kernel
  • Extensible operating systems
    • Spin, Vino, sandboxing, …
    • Modules
  • Configurable OS/Runtime
    • Scout, Think, Flux OSKit, eCos, TinyOS
    • SREAMS, x-kernel, CORDS
more info
More Info
  • “Highly Configurable Operating Systems for Ultrascale Systems,” Maccabe et al. In Proceedings of the First International Workshop on Operating Systems, Programming Environments and Management Tools for High-Performance Computing on Clusters (COSET-1), June 2004. (http://coset.irisa.fr/)
hpc architecture framework
HPC Architecture Framework
  • Next generation operating system must serve conventional architectures of today and future architectures towards nanoscale technology
    • Today: commodity clusters, MPPs, vector, multicore
    • Tomorrow: Heterogeneous, Stream, PIM, Reconfigurable
some basic assumptions
Some Basic Assumptions
  • Different programming and execution models will demand different optimizations in OS services for best performance
  • Micro-services may require more than a single node resource to accomplish function
  • Micro-services may perform management function on more than one node resource at a time
seven dimensional space of architectures
Seven-Dimensional Space of Architectures
  • Degree of Coupling
    • Relative bandwidth between external channel and local memory
    • Latency and latency hiding strategy support (e.g. multithreading)
  • Local state capacity
  • Overhead of context instantiation, switching, and synchronization
  • Namespace semantics and management towards single system image and virtualization
  • Resource allocation for memory objects (static versus dynamic)
  • Intrinsic model of execution
  • What to do when the application flatlines – exceptions and booting
programming models24
Programming Models
  • Distributed namespace
    • Shared nothing
  • Shared namespace
    • Shared addresses, heavyweight threads
  • Highly dynamic and fine-grained
    • Lightweight threads
    • In-memory synchronization
  • Need to keep an eye on new language developments ( Chpl, Fortress, X10)
additional considerations
Additional Considerations
  • OS services may consume parallel resources
  • Different applications may vary dramatically in terms of balance of resource usage and OS service request functionality
  • Architecture support may vary dramatically for efficient OS service functionality
  • “local” means all references and resources for an action are immediately available within a single cycle
initial focus
Initial Focus
  • Programming models
    • Distributed namespace (MPI)
    • Shared namespace (UPC)
    • Dynamic, fine-grained (ParalleX)
  • Architectures
    • Distributed memory (Red Storm)
    • Shared memory (Columbia)
    • PIM (MIND simulator)
currently brainstorming on micro services
Currently Brainstorming on Micro-services
  • Definition of a micro-service
  • Programming model for micro-services
  • What does a micro-service need?
  • What does a micro-service provide?
  • How does a micro-service behave?
  • How to support multiple implementations of the same micro-service?
  • What’s the smallest unit of activity that can be distributed?
  • Some micro-services may not be useful until combined with other micro-services
  • Can dynamic compilation serve as a possible implementation strategy for composing services
composability framework
Composability Framework
  • Model for composability of micro-services
  • Need more brainstorming to design the framework
  • Leverage OpenCatamount’s implementation details when the framework is defined
  • Open source version of Catamount
  • All Cray, Intel, and nCUBE proprietary code removed
  • Export control restriction lifted
  • Boots on a Dell box
  • Working on configuration and build environment
  • Likely will be released under Mozilla-style license
  • Should be up on Sandia download site real soon®
  • Port to a virtualization environment?
  • Programming model for micro-services
    • Q1FY06
  • Initial draft of the framework design and definition of micro-services
    • Q2FY06
  • Description of tools to do composition
    • Q3FY06
most pressing issue
Most Pressing Issue
  • What is the name of this project? 
  • Potential candidates: