8,324 research outputs found
Challenges Using the Linux Network Stack for Real-Time Communication
Starting in the early 2000s, human-in-the-loop (HITL) simulation groups at NASA and the Air Force Research Lab began using the Linux network stack for some real-time communication. More recently, SpaceX has adopted Ethernet as the primary bus technology for its Falcon launch vehicles and Dragon capsules. As the Linux network stack makes its way from ground facilities to flight critical systems, it is necessary to recognize that the network stack is optimized for communication over the open Internet, which cannot provide latency guarantees. The Internet protocols and their implementation in the Linux network stack contain numerous design decisions that favor throughput over determinism and latency. These decisions often require workarounds in the application or customization of the stack to maintain a high probability of low latency on closed networks, especially if the network must be fault tolerant to single event upsets
Challenges Using Linux as a Real-Time Operating System
Human-in-the-loop (HITL) simulation groups at NASA and the Air Force Research Lab have been using Linux as a real-time operating system (RTOS) for over a decade. More recently, SpaceX has revealed that it is using Linux as an RTOS for its Falcon launch vehicles and Dragon capsules. As Linux makes its way from ground facilities to flight critical systems, it is necessary to recognize that the real-time capabilities in Linux are cobbled onto a kernel architecture designed for general purpose computing. The Linux kernel contain numerous design decisions that favor throughput over determinism and latency. These decisions often require workarounds in the application or customization of the kernel to restore a high probability that Linux will achieve deadlines
Coz: Finding Code that Counts with Causal Profiling
Improving performance is a central concern for software developers. To locate
optimization opportunities, developers rely on software profilers. However,
these profilers only report where programs spent their time: optimizing that
code may have no impact on performance. Past profilers thus both waste
developer time and make it difficult for them to uncover significant
optimization opportunities.
This paper introduces causal profiling. Unlike past profiling approaches,
causal profiling indicates exactly where programmers should focus their
optimization efforts, and quantifies their potential impact. Causal profiling
works by running performance experiments during program execution. Each
experiment calculates the impact of any potential optimization by virtually
speeding up code: inserting pauses that slow down all other code running
concurrently. The key insight is that this slowdown has the same relative
effect as running that line faster, thus "virtually" speeding it up.
We present Coz, a causal profiler, which we evaluate on a range of
highly-tuned applications: Memcached, SQLite, and the PARSEC benchmark suite.
Coz identifies previously unknown optimization opportunities that are both
significant and targeted. Guided by Coz, we improve the performance of
Memcached by 9%, SQLite by 25%, and accelerate six PARSEC applications by as
much as 68%; in most cases, these optimizations involve modifying under 10
lines of code.Comment: Published at SOSP 2015 (Best Paper Award
Mixed-Criticality Scheduling with I/O
This paper addresses the problem of scheduling tasks with different
criticality levels in the presence of I/O requests. In mixed-criticality
scheduling, higher criticality tasks are given precedence over those of lower
criticality when it is impossible to guarantee the schedulability of all tasks.
While mixed-criticality scheduling has gained attention in recent years, most
approaches typically assume a periodic task model. This assumption does not
always hold in practice, especially for real-time and embedded systems that
perform I/O. For example, many tasks block on I/O requests until devices signal
their completion via interrupts; both the arrival of interrupts and the waking
of blocked tasks can be aperiodic. In our prior work, we developed a scheduling
technique in the Quest real-time operating system, which integrates the
time-budgeted management of I/O operations with Sporadic Server scheduling of
tasks. This paper extends our previous scheduling approach with support for
mixed-criticality tasks and I/O requests on the same processing core. Results
show the effective schedulability of different task sets in the presence of I/O
requests is superior in our approach compared to traditional methods that
manage I/O using techniques such as Sporadic Servers.Comment: Second version has replaced simulation experiments with real machine
experiments, third version fixed minor error in Equation 5 (missing a plus
sign
Astrophysical Supercomputing with GPUs: Critical Decisions for Early Adopters
General purpose computing on graphics processing units (GPGPU) is
dramatically changing the landscape of high performance computing in astronomy.
In this paper, we identify and investigate several key decision areas, with a
goal of simplyfing the early adoption of GPGPU in astronomy. We consider the
merits of OpenCL as an open standard in order to reduce risks associated with
coding in a native, vendor-specific programming environment, and present a GPU
programming philosophy based on using brute force solutions. We assert that
effective use of new GPU-based supercomputing facilities will require a change
in approach from astronomers. This will likely include improved programming
training, an increased need for software development best-practice through the
use of profiling and related optimisation tools, and a greater reliance on
third-party code libraries. As with any new technology, those willing to take
the risks, and make the investment of time and effort to become early adopters
of GPGPU in astronomy, stand to reap great benefits.Comment: 13 pages, 5 figures, accepted for publication in PAS
- …