Technology scaling and reliability challenges in the multicore era

Huard, V.; Cacho, F.; Federspiel, X.

doi:10.1109/irps.2013.6531975

Cited by 18 publications

(27 citation statements)

References 2 publications

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“…As multicore machines continue to scale up, the performance and reliability challenges on these architectures are becoming more severe because of the increased criticality of sharedresource contention and soft errors [2,3]. To realize the full potential of CMP platforms, we need to ensure that multi-threaded workloads not only execute e ciently and fast, but also correctly.…”

Section: List Of Tablesmentioning

confidence: 99%

“…On the other hand, a multi-threaded application can share multiple caches with multiple 2 Sibling threads are defined as the threads that are created from the same multi-threaded application. co-running threads, as shown in Figure 1.1(b), and contend for more than one cache with a multi-threaded co-runner.…”

Section: Resource Contentionmentioning

confidence: 99%

“…As the technology scaling continues, the size of the transistors shrinks each process generation, and the reliability of CMP platforms is becoming another critical issue [2,12]. In particular, systems are increasingly susceptible to transient faults or soft errors.…”

Section: Soft Errorsmentioning

confidence: 99%

“…Soft errors induced by alpha particles from packaging and atmospheric neutrons are a significant source of transient errors in modern microprocessors [15,2]. These transient faults arise from high energetic particles that generate electron-hole pairs when passing through any semiconductor device.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, the occurrence rate of these soft errors increases because of the higher number of smaller transistors on the system [12,2]. Therefore, as multicore machines continue to scale up to many-core machines, soft errors pose a significant risk for multicore processors and any systems-on-chip.…”

Section: Introductionmentioning

confidence: 99%

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ReSense: A Unified Framework for Improving Performance and Reliability in Multicore Architectures

Dey

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Chip-multiprocessors (CMPs) have become ubiquitous in modern computing and the mainstream architecture for various platforms, including laptops, desktops, and large server machines. As technology scaling continues and more transistors are accommodated on the chip, the number of cores on CMPs is growing, and multi-core machines are scaling up to many-core machines. With this multi-core scaling, two major problems arise: shared-resource contention and soft errors or transient faults. Shared-resource contention can degrade an application's performance significantly, and soft errors increase the probability of incorrect application execution and the production of visible errors. To realize the full potential of multi-and many-core platforms, it is critical to ensure that applications in a workload not only execute e ciently and fast, but also correctly.In this dissertation, we develop a novel, general, and unified framework, ReSense, to address several challenges on multicore architectures including performance optimization, reliability improvement, power and thermal management. The framework includes five components: a general characterization methodology, a characterization metric, a sensitivity score, a thread mapping algorithm, and a run-time system. An instance of the framework is applied in two phases: characterization and mapping. The characterization phase utilizes the general characterization methodology and characterization metric to identify application characteristics without considering any co-runner(s). It generates a resource-sensitivity score for each application in a workload. In the mapping phase, the run-time system uses a thread-mapping algorithm and the sensitivity scores of the applications in a workload to c Abstract d determine the thread-mappings that optimize the objective function of the targeted problem.To demonstrate the utility and e ectiveness of ReSense, we use it to address the problems of shared-resource contention and soft errors for multi-threaded applications. For the resource contention problem, the characterization methodology determines how a multi-threaded application's performance is a ected as it shares a resource in the memory hierarchy. A sensitivity score based on resource contention is produced for each application in a workload.The run-time system uses the resource-contention sensitivity scores and a thread-mapping algorithm to allocate threads from a workload to core to mitigate shared-resource contention, thus improving response time and throughput.For the soft error problem, the characterization methodology determines how a multithreaded application's vulnerability to soft errors in shared caches is a ected by its resource occupancy duration. A sensitivity score based on cache occupancy is produced for each application in a workload. The run-time system uses the cache-occupancy sensitivity scores and a thread-mapping algorithm to allocate workload threads to cores to reduce the occupancy in the shared caches, thus reducing cache vulnerability.Both minimizing...

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Section: List Of Tablesmentioning

confidence: 99%

Section: Resource Contentionmentioning

confidence: 99%

Section: Soft Errorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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