- Active Harmony
Ananta Tiwari, University of Maryland
Room 4140
Active Harmony framework permits automated runtime adaptation of
algorithms, data distribution and load balancing for parallel
applications. The framework exploits the tuning options specified
by parallel applications and adapts computation online based on
observed performance and changing conditions. In this demo, we will
present the Active Harmony system and describe the interface
used by programs to make applications tunable. We will use real
scientific applications for this purpose.
- Kernel Profiles for
User Applications
Via KerninstAPI Mike Brim, University of Wisconsin
Room 4140
This demonstration will highlight the ability of a KerninstAPI-based
profiler to dynamically observe the functions in the Linux kernel
executed on behalf of a given user application, and subsequently
produce a call graph with execution counts. Profiling via instrumentation
can often capture behavior not visible when observing execution using
periodic program counter sampling, as is used by tools such as OProfile.
- Root Cause Analysis of
Failures In Large-Scale
Computing Environments Alex Mirgorodskiy, University of Wisconsin
Room 4140
We demonstrate how self-propelled instrumentation can be combined
with machine-learning techniques to locate anomalies in distributed
environments. We use self-propelled instrumentation to collect
function-level traces for all nodes of a parallel application. When one
of the application nodes crashes or freezes, we recover collected traces
and save them to disk. Next, we identify the failed node by comparing
traces to each other with an automated outlier-detection technique.
Finally, we identify a function that is a likely cause of the failure
and report it to the analyst.
- Multiplatform Paradyn
Todd Miller, University of Wisconsin
Room 4140
We demonstrate Paradyn instrumenting an application with processes
running on IA-64, x86, and x86-64 machines. We let the Performance
Consultant automatically determine the nature of the bottleneck and
use the visualization tools to demonstrate its periodicity.
- Grid Resource Discovery
Using MRNet and the
Network Weather Service Dorian Arnold, University of Wisconsin
Room 4140
MRNet is a tree-based overlay network for scalable, efficient data
multicast and reduction services. The Network Weather Service (NWS)
monitors and dynamically forecasts the performance of network and
computational resources. This demonstration showcases the integration
of MRNet and the Network Weather Service into a matchmaking service
that could be used for applications like Grid scheduling. The MRNet
front-end allows users to specify resource constraints(e.g. Available
CPU > X MFLOPS && Available Memory > Y MB). NWS forecasts are computed
at the MRNet leaves which stream the results up the MRNet tree. Filters
in the MRNet tree execute constraint solvers that propagate the names
and properties of the resources that match the queries constraints.
- ParseThat - Exercising
the Dyninst Library Ray Chen, University of Maryland
Room 4139
We will demonstrate ParseThat, a tool that exercises the Dyninst
library on arbitrary binaries. A variety of targets will be
instrumented, including single-threaded, multi-threaded, and stripped
binaries. Target binaries will be accepted on request.
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