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Mapping and Scheduling of Dataflow Graphs - A Systematic Map

Dataflow is a natural way of modelling streaming applications, such as multimedia, networking and other signal processing applications. In order to cope with the computational and parallelism demands of such streaming applications, multiprocessor systems are replacing uniprocessor systems. Mapping and scheduling these applications on multiprocessor systems are crucial elements for efficient implem

MIMO Encoder and Decoder Design for Signal Estimation

We study the joint design of optimal linear MIMO encoders and decoders for filtering and transmission of a vector- valued signal over parallel Gaussian channels subject to a real- time constraint. The objective is to minimize the sum of the estimation error variances at the receiving end. The design problem is nonconvex, but it is shown that a global optimum can be found by solving a related two-s

Design Space Exploration of High-Level Stream Programs on Parallel Architectures

This paper presents a dataflow design methodology and an associated co-exploration environment, focusing on the optimization of buffer sizes. The approach is applicable to dynamic dataflow designs and its performance is presented and validated by experimental results on the porting of an MPEG-4 Simple Profile decoder to the STM STHORM manycore platform. For the purpose of this work, the decoder ha

Evaluation of Nonlinear Estimation Methods for Calibration of a Heat-Release Model

Model-based analysis of in-cylinder pressure sensor signals has been a key component for internal combustion engine research, diagnostics and controller development during the past decades. This analysis is often based on simple thermodynamic models of the in-cylinder processes. In order for the analysis to give accurate results, the models need to be sufficiently calibrated. This paper investigat

Integrating microorganism and macroorganism dispersal: modes, techniques and challenges with particular focus on co-dispersal.

Whatever their size and the ecosystem they live in, all organisms may disperse at some stage of their life cycle. Dispersal dynamics are to a varying extent dependent on organismal size, life history, ecological niche, survival capacities and phylogeny. Moves towards a synthesis in dispersal ecology have focused primarily on vertebrates and higher plants, yet recent studies suggest that the disper

Bonsai: Rapid Bounding Volume Hierarchy Generation using Mini Trees

We present an algorithm, called Bonsai, for rapidly building bounding volume hierarchies for ray tracing. Our method starts by computing midpoints of the triangle bounding boxes and then performs a rough hierarchical top-down split using the midpoints, creating triangle groups with tight bounding boxes. For each triangle group, a mini tree is built using an improved sweep SAH method. Once all mini

TURNUS: a Design Exploration Framework for Dataflow System Design

While research on the design of heterogeneous concurrent systems has a long and rich history, a unified design methodology and tool support has not emerged so far, and thus the creation of such systems remains a difficult, time-consuming and error-prone process. The absence of principled support for system evaluation and optimization at high abstraction levels makes the quality of the resulting im

Encoder and Decoder Design for Signal Estimation

In this paper, we study the joint design of optimal linear encoders and decoders for filtering and transmission of a signal over an additive Gaussian noise channel subject to a real-time constraint. The objective is to minimize the variance of the estimation error at the receiving end. The design problem is nonconvex, but it is shown that a global optimum can be found by solving a related two-stag

Auto-tuning Interactive Ray Tracing using an Analytical GPU Architecture Model

This paper presents a method for auto-tuning interactive ray tracing on GPUs using a hardware model. Getting full performance from modern GPUs is a challenging task. Workloads which require a guaranteed performance over several runs must select parameters for the worst performance of all runs. Our method uses an analyti- cal GPU performance model to predict the current frame’s render- ing time usi

Model-Based Deadtime Compensation of Virtual Machine Startup Times

Scaling the amount of resources allocated to an application according to the actual load is a challenging problem in cloud computing. The emergence of autoscaling techniques allows for autonomous decisions to be taken when to acquire or release resources. The actuation of these decisions is however affected by time delays. Therefore, it becomes critical for the autoscaler to account for this pheno

High-level Synthesis of Dataflow Programs for Signal Processing Systems

The growing complexity of signal processing algorithms and platforms poses significant challenges to design methods and implementation tools. High-level dataflow programs, such as those in MPEG's RVC-CAL language, provide abstraction and the opportunity for extensive design-space exploration, but they do raise the problem of efficient automatic synthesis to hardware and software. This paper presen