Splash-3: A properly synchronized benchmark suite for contemporary research

Sakalis, Christos; Leonardsson, Carl; Ros, Alberto

doi:10.1109/ispass.2016.7482078

Cited by 86 publications

(41 citation statements)

References 18 publications

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“…To evaluate DiMEM Simulator, a variety of HPC and cloud benchmarks were employed. HPC benchmarks involved Barnes, Volrend, and Raytrace of the Splash-3 benchmark suite [22], and FluidAnimate of the PARSEC benchmark suite [23]. The memcached-based Data Caching benchmark of the Cloud-Suite [24,25] benchmark suite for cloud services was employed as the cloud benchmark.…”

Section: Simulating Disaggregated Memorymentioning

confidence: 99%

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dReDBox: A Disaggregated Architectural Perspective for Data Centers

Alachiotis

Andronikakis

Papadakis

et al. 2018

Hardware Accelerators in Data Centers

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Data centers are currently constructed with fixed blocks (blades); the hard boundaries of this approach lead to suboptimal utilization of resources and increased energy requirements. The dReDBox (disaggregated Recursive Datacenter in a Box) project addresses the problem of fixed resource proportionality in next-generation, low-power data centers by proposing a paradigm shift toward finer resource allocation granularity, where the unit is the function block rather than the mainboard tray. This introduces various challenges at the system design level, requiring elastic hardware architectures, efficient software support and management, and programmable interconnect. Memory and hardware accelerators can be dynamically assigned to processing units to boost application performance, while high-speed, low-latency electrical and optical interconnect is a prerequisite for realizing the concept of data center disaggregation. This chapter presents the dReDBox hardware architecture and discusses design aspects of the software infrastructure for resource allocation and management. Furthermore, initial simulation and evaluation results for accessing remote, disaggregated memory are presented, employing benchmarks from the Splash-3 and the CloudSuite benchmark suites.

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Section: Simulating Disaggregated Memorymentioning

confidence: 99%

“…Workload profile for Raytrace (Splash-3 benchmark suite[22]), measured as the number of missed per kilo instruction (MPKI) per window. Workload profile for Data Caching (CloudSuite benchmark suite[25]), measured as the number of missed per kilo instruction (MPKI) per window.…”

mentioning

confidence: 99%

dReDBox: A Disaggregated Architectural Perspective for Data Centers

Alachiotis

Andronikakis

Papadakis

et al. 2018

Hardware Accelerators in Data Centers

View full text Add to dashboard Cite

show abstract

“…This section analyzes the xDRF regions found in applications from the Splash-3 [34] (a modernized, data-race-free version of the Splash-2 [39]) and Parsec-2.1 [7] benchmark suites with standard and simsmall inputs, respectively. We simulate the entire application and collect statistics corresponding to the parallel region of the applications (region of interest).…”

Section: Evaluation Of Xdrf Regionsmentioning

confidence: 99%

Automatic detection of extended data-race-free regions

Jimborean

Waern

Ekemark

et al. 2017

2017 IEEE/ACM International Symposium on Code Generation and Optimization (CGO)

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Data-race-free (DRF) parallel programming becomes a standard as newly adopted memory models of mainstream programming languages such as C++ or Java impose data-racefreedom as a requirement.We propose compiler techniques that automatically delineate extended data-race-free regions (xDRF), namely regions of code which provide the same guarantees as the synchronization-free regions (in the context of DRF codes). xDRF regions stretch across synchronization boundaries, function calls and loop back-edges and preserve the data-racefree semantics, thus increasing the optimization opportunities exposed to the compiler and to the underlying architecture. Our compiler techniques precisely analyze the threads' memory accessing behavior and data sharing in shared-memory, general-purpose parallel applications and can therefore infer the limits of xDRF code regions.We evaluate the potential of our technique by employing the xDRF region classification in a state-of-the-art, dualmode cache coherence protocol. Larger xDRF regions reduce the coherence bookkeeping and enable optimizations for performance (6.8%) and energy efficiency (11.7%) compared to a standard directory-based coherence protocol.

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“…To evaluate the runtime performance of Rain in multi-core machines, we run the SPLASH-3 [46] multi-core benchmark with a 4-core CPU and summarize the results in Figure 7. The geometric mean of runtime overhead (logging+recording) is 5.35%, and Rain is able to faithfully replay all the benchmarks without divergence.…”

Section: Performancementioning

confidence: 99%

Rain

Yang

Lee

Downing

et al. 2017

Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security

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As modern attacks become more stealthy and persistent, detecting or preventing them at their early stages becomes virtually impossible. Instead, an attack investigation or provenance system aims to continuously monitor and log interesting system events with minimal overhead. Later, if the system observes any anomalous behavior, it analyzes the log to identify who initiated the attack and which resources were affected by the attack and then assess and recover from any damage incurred. However, because of a fundamental tradeoff between log granularity and system performance, existing systems typically record system-call events without detailed program-level activities (e.g., memory operation) required for accurately reconstructing attack causality or demand that every monitored program be instrumented to provide program-level information. To address this issue, we propose Rain, a Refinable Attack INvestigation system based on a record-replay technology that records system-call events during runtime and performs instructionlevel dynamic information flow tracking (DIFT) during on-demand process replay. Instead of replaying every process with DIFT, Rain conducts system-call-level reachability analysis to filter out unrelated processes and to minimize the number of processes to be replayed, making inter-process DIFT feasible. Evaluation results show that Rain effectively prunes out unrelated processes and determines attack causality with negligible false positive rates. In addition, the runtime overhead of Rain is similar to existing systemcall level provenance systems and its analysis overhead is much smaller than full-system DIFT.

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Splash-3: A properly synchronized benchmark suite for contemporary research

Cited by 86 publications

References 18 publications

dReDBox: A Disaggregated Architectural Perspective for Data Centers

dReDBox: A Disaggregated Architectural Perspective for Data Centers

Automatic detection of extended data-race-free regions

Rain

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