The future technologies team at CCS plays an important role in the development of leadership-class computing.
Scientific
applications—computer codes that enable supercomputers
to run calculations on huge amounts of data to solve complex problems—will
help researchers make important scientific discoveries more
quickly if the codes are run on more powerful unclassified supercomputers
than exist today. The goal of the Department of Energy is to increase
by a factor of 100 the computing capability available to support
open scientific research. Such leadership-class computing would
reduce the time required to simulate complex systems, such as future
climate, from years to days.
The future
technologies team at DOE's Center for Computational
Sciences at ORNL plays an important role in the development of leadership-class
computing. By investigating the continuously evolving core technologies
critical to leadership-class systems, the future technologies team led
by Jeffrey Vetter is identifying technologies that satisfy the performance
requirements of DOE applications. Furthermore, with their intimate
knowledge of the applications, software, and hardware, this team
works cooperatively with vendors to ensure that the next generation
of computing technology meets the requirements of DOE mission applications.
Initially, the future technologies team is focusing on four application
areas: biology, climate, fusion, and nanoscience.
In collaboration
with universities and other government labs, the future technologies team evaluates new computer architectures, tracks and
helps design future architectures, gathers contemporary application-driven
systems requirements, develops performance prediction capabilities
for leadership-class computing, and assesses the state of software for
these systems.
Evaluating New Architectures
New computer
architectures are evolving at a rapid rate. The future technologies
team studies these new architectures and evaluates the suitability
of each architecture to important ORNL applications. In particular,
the overall goal of this strategy is to identify each system's architectural
strengths and weaknesses in the context of these important applications.
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The Cray X1 outperforms the other CCS supercomputers in the amount of
data passed both ways between the processors and memory.
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Then, in cooperation with users and other government agencies, the
team uses the gathered evidence to assist vendors in the design of
future architectures.
Recently,
CCS evaluated several systems, including the Cray X1,
the SGI Altix 3000, and the IBM Power4 cluster. In the short term, the
future technologies team will evaluate the Cray Red Storm system, the
IBM Blue Gene/L system, and the IBM Federation interconnect. Evaluations
on the horizon will focus on the Cray X2, the IBM Power5, and the DARPA
HPCS systems from Cray, IBM, and Sun Microsystems. In addition, the future
technologies team is evaluating individual core technologies for
leadership-class computing including processors, interconnects, memory
subsystems, storage subsystems, system software, and programming
models. Core technologies that the team is considering include the IBM's
Federation interconnect, Infiniband interconnect, and processors
for reconfigurable computing.
Simply
put, CCS constantly surveys the computing landscape for future architectures
that may offer orders-of-magnitude improvements in leadership-class
computing. Thus, the future technologies team continues to track and
evaluate evolving technologies such as system-on-a-chip (SOC), processor-in-memory
(PIM), simultaneous multithreading, smart networks, optical interconnects,
reconfigurable computers,
and streaming supercomputers.
In some cases, these technologies could provide CCS users with tremendous
improvements in their scientific productivity
because of higher performance, lower costs of ownership, and increased
reliability and availability. Using evidence gathered by the future
technologies team, CCS makes informed decisions about which
speculative architectures to endorse, fund, and procure.
Application-Driven System Requirements
In addition
to its evaluation activities, the future technologies team maintains
an ongoing, contemporary set of application-driven systems requirements
to use for procurements and for feedback to architects.
In conjunction with the user communities, the group has identified
major classes of scientific applications likely to dominate leadership-class
system usage over the next five to ten years. Within each area, the CCS
team investigates the machine properties (e.g., floating-point performance,
memory, interconnect performance, input/output capability, and mass
storage capacity) needed to enable major progress in each application
class. This information helps CCS address major hardware, software,
and algorithmic challenges to the effective use of leader-ship-class
computing systems.
Predicting Performance
Generating
application-driven systems requirements and performing evaluations
on existing systems provide some insight into which architectures best
match CCS workloads. However, the best possibility for furthering the
understanding of performance phenomena and for assisting in intelligent
procurement selections may lie in the technique of performance modeling.
By having core competencies in the future technologies team for modeling,
measurement, and simulation of computer systems themselves, CCS
has at its disposal not only
performance information about
existing systems,
but also the capability
to speculate
about future architectures.
With this
information, it is
possible to predict
the performance
achieved by a future
system even though
that system is much
larger than systems
available today.
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Core technologies for ultrascale computing.
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Scalable
Software
Software
infrastructure plays a critical role in reducing the time needed for
computational scientists to solve a problem
across all phases of application development
and use. Simply addressing algorithms
and architectures is insufficient to
ensure success on a leadership-class computer.
First, software programming models
and design must efficiently harness the
underlying computer hardware to ensure
reasonable execution performance. Second,
software will play an important role
in the reliability and availability of these
new architectures. Applications and system
software must adapt to and overcome
faults in the underlying hardware. Third,
scientists' productivity is often at odds with
current software development techniques.
In particular, the current methods of constructing,
optimizing, and using massively
parallel scientific applications can be difficult,
tedious, and inefficient.
The future
technologies team in CCS is in a critical position to evaluate and
experiment with alternative technologies on
leadership-class computers. Scalable, reliable system software is vital
to the operation of a leadership-class platform. This software will provide
baseline services such as operating systems, file systems, job and task
scheduling, communication (MPI) libraries, resource management, configuration
management, security, programming model support, and fault management.
Given the possible scale of new systems that will have thousands
to millions of processors, it is imperative that these services be efficient,
scalable, and reliable. Because the requirements for scientific computing
on this scale differ drastically from the requirements for commodity
operating systems, the future technologies team is evaluating software
environments to judge the scalability and reliability of system software
and the associated programming environments and tools. Using this
information, the team maintains a list of critical software requirements
and undertakes research to solve these problems, in collaboration
with universities, vendors, and other DOE national laboratories.
Ultimately,
a goal of the future technologies team is to ensure that
users can fully capitalize on leadership-class hardware and software
to boost scientific productivity in meeting DOE missions. In this
role of pathfinder for CCS, the future technologies team explores
new technologies and interacts with users, researchers, and vendors to
drive promising technologies forward.
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