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Partitioning and Optimization of High-Level Stream Applications for Multi-Clock-Domain Architectures

In this paper we propose a design methodology to partition dataflow applications on a multi clock domain architecture. This work shows how starting from a high level dataflow representation of a dynamic program it is possible to reduce the overall power consumption without impacting the performances. Two different approaches are illustrated, both based on the post-processing and analysis of the ca

Sensing and Classification Using Massive MIMO : A Tensor Decomposition-Based Approach

Wireless-based activity sensing has gained significant attention due to its wide range of applications. We investigate radio-based multi-class classification of human activities using massive multiple-input multiple-output (MIMO) channel measurements in line-of-sight and non line-of-sight scenarios. We propose a tensor decomposition-based algorithm to extract features by exploiting the complex cor

Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding

The min-sum (MS) and approximate-min* (a-min*) algorithms are alternatives of the belief propagation (BP) algorithm for decoding low-density parity-check (LDPC) codes. To lower the BP decoding complexity, both algorithms compute two magnitudes at each check node (CN) and pass them to the neighboring variable nodes (VNs).In this work we propose a new algorithm, ga-min*, that generalizes the MS and

27.5-29.5 GHz Switched Array Sounder for Dynamic Channel Characterization: Design, Implementation and Measurements

A pre-requisite for the design of wireless systems is the understanding of the propagation channel. While a wealth of propagation knowledge exists for bands below 6 GHz, the same can not be said for bands approaching millimeter-wave frequencies. In this paper, we present the design, implementation and measurement-based verification of a re-configurable 27.5-29.5 GHz channel sounder for measuring d

Initial Analysis of Dynamic Panel Activation for Large Intelligent Surfaces

Large intelligent surfaces (LIS) have the potential to be the beyond-massive-MIMO solution, even further improving spectral efficiency, coverage, reliability and other performance measures. They also open up for entirely new services, such as precise localization, environment sensing, and wireless energy transfer. By constructing larger surfaces as a grid of panels, we can activate and deactivate

SAH guided spatial split partitioning for fast BVH construction

We present a new SAH guided approach to subdividing triangles as the scene is coarsely partitioned into smaller sets of spatiallycoherent triangles. Our triangle split approach is integrated into the partitioning stage of a fast BVH construction algorithm, butmay as well be used as a stand alone pre-split pass. Our algorithm significantly reduces the number of split triangles comparedto previous m

Implementing a streaming application on a processor array : A case study on the Epiphany architecture

This paper reports on a case study in which an at- size application is ported onto a commercially available processor array. Its purpose is threefold: (1) Determine the suitability of processor arrays for this kind of application. (2) Develop a runtime software infrastructure that supports streaming applications on processor arrays. (3) Gather data and insights into the resulting system performanc

Support for Data Parallelism in the CAL Actor Language

With the arrival of heterogeneous manycores comprising various features to support task, data and instruction-level parallelism, developing applications that take full advantage of the hardware parallel features has become a major challenge. In this paper, we present an extension to our CAL compilation framework (CAL2Many) that supports data parallelism in the CAL Actor Language. Our compilation f

Knee Injury and Osteoarthritis Outcome Score (KOOS) - Development of a self-administered outcome measure

There is broad consensus that good outcome measures are needed to distinguish interventions that are effective from those that are not. This task requires standardized, patient-centered measures that can be administered at a low cost. We developed a questionnaire to assess short- and long-term patient-relevant outcomes following knee injury, based on the WOMAC Osteoarthritis Index, a literature re

Optimal Linear Joint Source-Channel Coding with Delay Constraint

The problem of joint source-channel coding is considered for a stationary remote (noisy) Gaussian source and a Gaussian channel. The encoder and decoder are assumed to be causal and their combined operations are subject to a delay constraint. It is shown that, under the mean-square error distortion metric, an optimal encoder-decoder pair from the linear and time-invariant (LTI) class can be found

A Compressed Depth Cache

We propose a depth cache that keeps the depth data in compressed format, when possible. Compared to previous work, this requires a more flexible cache implementation, where a tile may occupy a variable number of cache lines depending on whether it can be compressed or not. The advantage of this is that the effective cache size increases proportionally to the compression ratio. We show that the dep

Coarse Pixel Shading

We present a novel architecture for flexible control of shading rates in a GPU pipeline, and demonstrate substantially reduced shading costs for various applications. We decouple shading and visibility by restricting and quantizing shading rates to a finite set of screen-aligned grids, leading to simpler and fewer changes to the GPU pipeline compared to alternative approaches. Our architecture int

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