Engineering topics

Fiala, David J

Publications and source records attributed to Fiala, David J.

3 records

DOE OSTI2013

Detection and Correction of Silent Data Corruption for Large-Scale High-Performance Computing

Faults have become the norm rather than the exception for high-end computing on clusters with 10s/100s of thousands of cores. Exacerbating this situation, some of these faults remain undetected, manifesting themselves as silent errors that corrupt memory while applications continue to operate and report incorrect results. This paper studies the potential for redundancy to both detect and correct soft errors in MPI message-passing applications. Our study investigates the challenges inherent to detecting soft errors within MPI application while providing transparent MPI redundancy. By assuming a model wherein corruption in application data manifests itself by producing differing MPI message data between replicas, we study the best suited protocols for detecting and correcting MPI data that is the result of corruption. To experimentally validate our proposed detection and correction protocols, we introduce RedMPI, an MPI library which resides in the MPI profiling layer. RedMPI is capable of both online detection and correction of soft errors that occur in MPI applications without requiring any modifications to the application source by utilizing either double or triple redundancy. Our results indicate that our most efficient consistency protocol can successfully protect applications experiencing even high rates of silent data corruption with runtime overheads between 0% and 30% as compared to unprotected applications without redundancy. Using our fault injector within RedMPI, we observe that even a single soft error can have profound effects on running applications, causing a cascading pattern of corruption in most cases causes that spreads to all other processes. RedMPI's protection has been shown to successfully mitigate the effects of soft errors while allowing applications to complete with correct results even in the face of errors.

Fiala, David J↗

DOE OSTI2012

A Tunable, Software-based DRAM Error Detection and Correction Library for HPC

Proposed exascale systems will present a number of considerable resiliency challenges. In particular, DRAM soft-errors, or bit-flips, are expected to greatly increase due to the increased memory density of these systems. Current hardware-based fault-tolerance methods will be unsuitable for addressing the expected soft error frequency rate. As a result, additional software will be needed to address this challenge. In this paper we introduce LIBSDC, a tunable, transparent silent data corruption detection and correction library for HPC applications. LIBSDC provides comprehensive SDC protection for program memory by implementing on-demand page integrity verification. Experimental benchmarks with Mantevo HPCCG show that once tuned, LIBSDC is able to achieve SDC protection with 50\% overhead of resources, less than the 100\% needed for double modular redundancy.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2012

Combining Partial Redundancy and Checkpointing for HPC

Today's largest High Performance Computing (HPC) systems exceed one Petaflops (10^15 floating point operations per second) and exascale systems are projected within seven years. But reliability is becoming one of the major challenges faced by exascale computing. With billion-core parallelism, the mean time to failure is projected to be in the range of minutes or hours instead of days. Failures are becoming the norm rather than the exception during execution of HPC applications. Current fault tolerance techniques in HPC focus on reactive ways to mitigate faults, namely via checkpoint and restart (C/R). Apart from storage overheads, C/R-based fault recovery comes at an additional cost in terms of application performance because normal execution is disrupted when checkpoints are taken. Studies have shown that applications running at a large scale spend more than 50\% of their total time saving checkpoints, restarting and redoing lost work. Redundancy is another fault tolerance technique, which employs redundant processes performing the same task. If a process fails, a replica of it can take over its execution. Thus, redundant copies can decrease the overall failure rate. The downside of redundancy is that extra resources are required and there is an additional overhead on communication and synchronization. This work contributes a model and analyzes the benefit of C/R in coordination with redundancy at different degrees to minimize the total wallclock time and resources utilization of HPC applications. We further conduct experiments with an implementation of redundancy within the MPI layer on a cluster. Our experimental results confirm the benefit of dual and triple redundancy - but not for partial redundancy - and show a close fit to the model. At 80,000 processes, dual redundancy requires twice the number of processing resources for an application but allows two jobs of 128 hours wallclock time to finish within the time of just one job without redundancy. For narrow ranges of processor counts, partial redundancy results in the lowest time. Once the count exceeds 770, 000, triple redundancy has the lowest overall cost. Thus, redundancy allows one to trade-off additional resource requirements against wallclock time, which provides a tuning knob for users to adapt to resource availabilities.

Elliott, James↗