OpenCL Application Auto-tuning and Run-Time Resource Management for Multi-core Platforms

Gadioli, Davide; Libutti, Simone; Massari, Giuseppe; Paone, Edoardo; Scandale, Michele; Bellasi, Patrick; Palermo, Gianluca; Zaccaria, Vittorio; Agosta, Giovanni; Fornaciari, William; Silvano, Cristina

doi:10.1109/ispa.2014.25

Cited by 6 publications

(5 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The work in [28] provided a generic tool for performance measurement of OpenCL programs. In [29], the authors proposed a framework combining OpenCL application auto-tuning and runtime resource management. The study in [30] presented a transparent OpenCL overlay called Helium, for inter-and intra-kernel optimisation.…”

Section: B Adas Applications On Heterogeneous Platformsmentioning

confidence: 99%

Performance Optimisation of Parallelized ADAS Applications in FPGA-GPU Heterogeneous Systems: A Case Study With Lane Detection

Wang

Huang

Knoll

2019

IEEE Trans. Intell. Veh.

View full text Add to dashboard Cite

The explosive growth of massive data captured by various sensors on modern vehicles has impelled the deployment of Commercial Off-The-Shelf (COTS) accelerators for the research and development of Advanced Driver Assistance Systems (ADAS). Although the advent of cross-platform programming framework such as Open Computing Language (OpenCL) facilitates the programmability of ADAS applications on heterogeneous devices, the performance portability is still vulnerable and subject to different hardware implementations by the heterogeneous manufacturers. With this issue in mind, in this article we propose a detailed procedure that helps guide the performance optimisation of parallelized ADAS applications in an FPGA-GPU combined heterogeneous system. Taking two different lane detection applications as case studies, we provide one intra-accelerator and two interaccelerator optimisation methods, as well as both FPGA-specific and application-oriented optimisation strategies, to boost the program runtime performance. Experiment results on a heterogeneous platform with COTS FPGA and GPU components reveal that the optimal designs generated from the procedure can improve the runtime performance of the two applications by an average of 109.21% and 83.48% over the native parallel implementations, respectively.

show abstract

Section: B Adas Applications On Heterogeneous Platformsmentioning

confidence: 99%

Performance Optimisation of Parallelized ADAS Applications in FPGA-GPU Heterogeneous Systems: A Case Study With Lane Detection

Wang

Huang

Knoll

2019

IEEE Trans. Intell. Veh.

View full text Add to dashboard Cite

show abstract

“…Currently the tool is under construction and some features like memory and buffer routines are not implemented yet. In [7], the authors proposed a framework combing OpenCL application auto-tuning and runtime resource management. Authors in [8] presented a transparent OpenCL overlay called Helium, for inter-and intra-kernel optimization.…”

Section: Related Workmentioning

confidence: 99%

Improving the performance of ADAS application in heterogeneous context: A case of lane detection

Wang

Cui

Huang

et al. 2017

2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)

View full text Add to dashboard Cite

This paper investigates the optimization of OpenCLbased ADAS applications in heterogeneous context. In particular, we take the widely-used lane detection algorithm (LDA) as a case study. The application is profiled to identify the performance bottlenecks and then three optimization strategies are adopted. On the kernel side, the parallel granularity is regulated via compute unit replication and loop unrolling. On the host side, the kernel API function calls are scheduled in an interleaved manner to overlap the accelerator execution time. Moreover, the computation workload of the algorithm is tuned by dynamically adjusting the processed image ROI size. Experimental results reveal that the optimized implementation can achieve an average 2.27x speedup when compared with the naive parallel application.

show abstract

“…Some implementations take a two-staged approach [28], where several codelets are generated for the target platform at installation which are then used at runtime to build the search space of implementation variants. Only recently, approaches which attempt to tune general purpose applications, similar to our effort, have started to emerge, for example using higher-level languages like OmpSs [29] and HMPP [30] or by allowing developers to expose tuning parameters [31].…”

Section: Related Workmentioning

confidence: 99%

Tuning OpenCL Applications with the Periscope Tuning Framework

Bajrovic

Mijakovic

Dokulil

et al. 2016

2016 49th Hawaii International Conference on System Sciences (HICSS)

View full text Add to dashboard Cite

Due to the complexity and diversity of new parallel architectures automatic tuning of parallel applications has become increasingly important for achieving acceptable performance levels as well as performance portability. The European AutoTune project developed a tuning framework which closely integrates and automates performance analysis and performance tuning. The Periscope Tuning Framework relies on a flexible plugin mechanism providing tuning plugins for different tuning aspects. This paper presents plugins for tuning the execution time of OpenCL kernels on three different architectures, namely standard multicore CPUs, Xeon Phi coprocessors, and GPUs. We present OpenCL tuning via the flags used during offline kernel compilation as well as through the selection of the most appropriate NDRange configuration, which defines the organization of parallel threads used for kernel execution. Both tuning plugins show significant performance impact and a clear dependence on the target architecture and thus improve performance portability via automatic tuning.

show abstract

OpenCL Application Auto-tuning and Run-Time Resource Management for Multi-core Platforms

Cited by 6 publications

References 16 publications

Performance Optimisation of Parallelized ADAS Applications in FPGA-GPU Heterogeneous Systems: A Case Study With Lane Detection

Performance Optimisation of Parallelized ADAS Applications in FPGA-GPU Heterogeneous Systems: A Case Study With Lane Detection

Improving the performance of ADAS application in heterogeneous context: A case of lane detection

Tuning OpenCL Applications with the Periscope Tuning Framework

Contact Info

Product

Resources

About