TFlux: A Portable Platform for Data-Driven Multithreading on Commodity Multicore Systems

Stavrou, Kyriakos; Nikolaides, Marios; Pavlou, Demos; Arandi, Samer; Evripidou, Paraskevas; Trancoso, Pedro

doi:10.1109/icpp.2008.74

Cited by 30 publications

(23 citation statements)

References 12 publications

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“…More recently, Evripidou et al proposed a new programming model called Data-Driven Multithreading (DDM) [15], based on dataflow model of execution. Subsequent works include tools for exploiting DDM on commodity multicores [19], [20], and the usage of DDM in HPC [4]. Targeting function level parallelism, Gupta and Sohi applied dataflow analysis to generate multithreaded code from imperative programs [8].…”

Section: Related Workmentioning

confidence: 99%

An Approach for Direct Dataflow Execution on Contemporary Multicore Systems

Loghin

Tudor

Teo

2013

2013 Data-Flow Execution Models for Extreme Scale Computing

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Abstract-Traditionally, imperative programming uses a series of state-based operands to model control-flow and, as a result, suffers from the well-known von Neumann bottleneck. In contrast, dataflow programs are driven only by the availability of instruction operands. However, the lack of mainstream dataflow hardware hinders direct dataflow instruction execution. On the other hand, direct execution of dataflow programs on von Neumann machines incurs a high performance cost. In this paper, we present preliminary results on the direct execution of dataflow programs on multicore systems through emulation of taggedtokens mechanism. Compared with direct translation of SISAL programs to C code, we achieved a speedup of 44 for CPUintensive applications and 22 for memory-bounded applications on a 48-cores AMD NUMA system.

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Section: Related Workmentioning

confidence: 99%

An Approach for Direct Dataflow Execution on Contemporary Multicore Systems

Loghin

Tudor

Teo

2013

2013 Data-Flow Execution Models for Extreme Scale Computing

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“…[2]. The applications have been written in StarSs [3], a task-level data-flow programming model similar to Cilk [4], RapidMind [5], Sequoia [6], and Tflux-DDM [7]. These programming models let the programmer write a seemingly sequential program, and annotate the input and output parameters of functions that can potentially execute as parallel tasks.…”

Section: Introductionmentioning

confidence: 99%

Interleaving granularity on high bandwidth memory architecture for CMPs

Cabarcas

Rico

Etsion

et al. 2010

2010 International Conference on Embedded Computer Systems: Architectures, Modeling and Simulation

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Abstract-Memory bandwidth has always been a critical factor for the performance of many data intensive applications. The increasing processor performance, and the advert of single chip multiprocessors have increased the memory bandwidth demands beyond what a single commodity memory device can provide. The immediate solution is to use more than one memory device, and interleave data across them so they can be used in parallel as if they were a single device of higher bandwidth.In this paper we showed that fine-grain memory interleaving on the evaluated many-core architectures with many DRAM channels was critical to achieve high memory bandwidth efficiency. Our results showed that performance can degrade up to 50% due to achievable bandwidths being far from the maximum installed.

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“…To avoid this issue it would be interesting to explore alternative parallel execution using implementations that are more efficient (e.g. the TFlux [13] model which has minimal synchronization and runtime overheads).…”

Section: General-purpose Multi-core Architecturesmentioning

confidence: 99%

New records, replacements, reinstatements and four new species in the Radula parvitexta and R. ventricosa species groups (Jungermanniopsida) in Australia: cases of mistaken identity

Renner

Devos

Brown

et al. 2013

Aust. Systematic Bot.

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We are currently faced with the situation where applications have increasing computational demands and there is a wide selection of parallel processor systems. In this paper we focus on exploiting fine-grain parallelism for a demanding Bioinformatics application -MrBayes -and its Phylogenetic Likelihood Functions (PLF) using different architectures. Our experiments compare side-by-side the scalability and performance achieved using general-purpose multi-core processors, the Cell/BE, and Graphics Processor Units (GPU). The results indicate that all processors scale well for larger computation and data sets. Also, GPU and Cell/BE processors achieve the best improvement for the parallel code section. Nevertheless, data transfers and the execution of the serial portion of the code are the reasons for their poor overall performance. The general-purpose multi-core processors prove to be simpler to program and provide the best balance between an efficient parallel and serial execution, resulting in the largest speedup.

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TFlux: A Portable Platform for Data-Driven Multithreading on Commodity Multicore Systems

Cited by 30 publications

References 12 publications

An Approach for Direct Dataflow Execution on Contemporary Multicore Systems

An Approach for Direct Dataflow Execution on Contemporary Multicore Systems

Interleaving granularity on high bandwidth memory architecture for CMPs

New records, replacements, reinstatements and four new species in the Radula parvitexta and R. ventricosa species groups (Jungermanniopsida) in Australia: cases of mistaken identity

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