Developing Efficient Discrete Simulations on Multicore and GPU Architectures

In this paper we show how to efficiently implement parallel discrete simulations on multicoreandGPUarchitecturesthrougharealexampleofanapplication: acellularautomatamodel of laser dynamics. We describe the techniques employed to build and optimize the implementations using OpenMP and CUDA frameworks. We have evaluated the performance on two different hardware platforms that represent different target market segments: high-end platforms for scientific computing, using an Intel Xeon Platinum 8259CL server with 48 cores, and also an NVIDIA Tesla V100GPU,bothrunningonAmazonWebServer(AWS)Cloud;and on a consumer-oriented platform, using an Intel Core i9 9900k CPU and an NVIDIA GeForce GTX 1050 TI GPU. Performance results were compared and analyzed in detail. We show that excellent performance and scalability can be obtained in both platforms, and we extract some important issues that imply a performance degradation for them. We also found that current multicore CPUs with large core numbers can bring a performance very near to that of GPUs, and even identical in some cases.Ministerio de Economía, Industria y Competitividad, Gobierno de España (MINECO), and the Agencia Estatal de Investigación (AEI) of Spain, cofinanced by FEDER funds (EU) TIN2017-89842

Spike-based control monitoring and analysis with Address Event Representation

Neuromorphic engineering tries to mimic biological information processing. Address-Event Representation (AER) is a neuromorphic communication protocol for spiking neurons between different chips. We present a new way to drive robotic platforms using spiking neurons. We have simulated spiking control models for DC motors, and developed a mobile robot (Eddie) controlled only by spikes. We apply AER to the robot control, monitoring and measuring the spike activity inside the robot. The mobile robot is controlled by the AER-Robot tool, and the AER information is sent to a PC using the USBAERmini2 interface.Junta de Andalucía P06-TIC-01417Ministerio de Educación y Ciencia TEC2006-11730-C03-0

High-Efficient Parallel CAVLC Encoders on Heterogeneous Multicore Architectures

This article presents two high-efficient parallel realizations of the context-based adaptive variable length coding (CAVLC) based on heterogeneous multicore processors. By optimizing the architecture of the CAVLC encoder, three kinds of dependences are eliminated or weaken, including the context-based data dependence, the memory accessing dependence and the control dependence. The CAVLC pipeline is divided into three stages: two scans, coding, and lag packing, and be implemented on two typical heterogeneous multicore architectures. One is a block-based SIMD parallel CAVLC encoder on multicore stream processor STORM. The other is a component-oriented SIMT parallel encoder on massively parallel architecture GPU. Both of them exploited rich data-level parallelism. Experiments results show that compared with the CPU version, more than 70 times of speedup can be obtained for STORM and over 50 times for GPU. The implementation of encoder on STORM can make a real-time processing for 1080p @30fps and GPU-based version can satisfy the requirements for 720p real-time encoding. The throughput of the presented CAVLC encoders is more than 10 times higher than that of published software encoders on DSP and multicore platforms

The JKind Model Checker

JKind is an open-source industrial model checker developed by Rockwell Collins and the University of Minnesota. JKind uses multiple parallel engines to prove or falsify safety properties of infinite state models. It is portable, easy to install, performance competitive with other state-of-the-art model checkers, and has features designed to improve the results presented to users: inductive validity cores for proofs and counterexample smoothing for test-case generation. It serves as the back-end for various industrial applications.Comment: CAV 201

Open semantic service networks

Online service marketplaces will soon be part of the economy to scale the provision of specialized multi-party services through automation and standardization. Current research, such as the *-USDL service description language family, is already defining the basic building blocks to model the next generation of business services. Nonetheless, the developments being made do not target to interconnect services via service relationships. Without the concept of relationship, marketplaces will be seen as mere functional silos containing service descriptions. Yet, in real economies, all services are related and connected. Therefore, to address this gap we introduce the concept of open semantic service network (OSSN), concerned with the establishment of rich relationships between services. These networks will provide valuable knowledge on the global service economy, which can be exploited for many socio-economic and scientific purposes such as service network analysis, management, and control