Reduced Aggregate Scattering Operators for Path Tracing

Aggregate scattering operators (ASOs) describe the overall scattering behavior of an asset (i.e., an object or volume, or collection thereof) accounting for all orders of its internal scattering. We propose a practical way to precompute and compactly store ASOs and demonstrate their ability to accelerate path tracing. Our approach is modular avoiding costly and inflexible scene‐dependent precomputation. This is achieved by decoupling light transport within and outside of each asset, and precomputing on a per‐asset level. We store the internal transport in a reduced‐dimensional subspace tailored to the structure of the asset geometry, its scattering behavior, and typical illumination conditions, allowing the ASOs to maintain good accuracy with modest memory requirements. The precomputed ASO can be reused across all instances of the asset and across multiple scenes. We augment ASOs with functionality enabling multi‐bounce importance sampling, fast short‐circuiting of complex light paths, and compact caching, while retaining rapid progressive preview rendering. We demonstrate the benefits of our ASOs by efficiently path tracing scenes containing many instances of objects with complex inter‐reflections or multiple scattering.     

A Parallelization Approach for Hard Real-Time Systems and Its Application on Two Industrial Programs

Applications in industry often have grown and improved over many years. Since their performance demands increase, they also need to benefit from the availability of multi-core processors. However, a reimplementation from scratch and even a restructuring of these industrial applications is very expensive, often due to high certification efforts. Therefore, a strategy for a systematic parallelization of legacy code is needed. We present a parallelization approach for hard real-time systems, which ensures a high reusage of legacy code and preserves timing analysability. To show its applicability, we apply it on the core algorithm of an avionics application as well as on the control program of a large construction machine. We create models of the legacy programs showing the potential of parallelism, optimize them and change the source codes accordingly. The parallelized applications are placed on a predictable multi-core processor with up to 18 cores. For evaluation, we compare the worst case execution times and their speedups. Furthermore, we analyse limitations coming up at the parallelization process.     

Parsing human skeletons in an operating room

Multiple human pose estimation is an important yet challenging problem. In an operating room (OR) environment, the 3D body poses of surgeons and medical staff can provide important clues for surgical workflow analysis. For that purpose, we propose an algorithm for localizing and recovering body poses of multiple human in an OR environment under a multi-camera setup. Our model builds on 3D Pictorial Structures and 2D body part localization across all camera views, using convolutional neural networks (ConvNets). To evaluate our algorithm, we introduce a dataset captured in a real OR environment. Our dataset is unique, challenging and publicly available with annotated ground truths. Our proposed algorithm yields to promising pose estimation results on this dataset.     

Computational performance of a parallelized three-dimensional high-order spectral element toolbox

In this paper, a comprehensive performance review of an MPI-based high-order three-dimensional spectral element method C++ toolbox is presented. The focus is put on the performance evaluation of several aspects with a particular emphasis on the parallel efficiency. The performance evaluation is analyzed with the help of a time prediction model based on a parameterization of the application and the hardware resources. Two tailor-made benchmark cases in computational fluid dynamics (CFD) are introduced and used to carry out this review, stressing the particular interest for clusters with up to thousands of cores. Some problems in the parallel implementation have been detected and corrected. The theoretical complexities with respect to the number of elements, to the polynomial degree, and to communication needs are correctly reproduced. It is concluded that this type of code has a nearly perfect speedup on machines with thousands of cores, and is ready to make the step to next-generation petaFLOP machines.     

Simulations, models, and testbeds: A mutual catalysis

Recent developments in the area of decentralized and infrastructureless systems opened avenues for novel applications. Along with these new technologies, new questions regarding their operational bounds in terms of e.g. scalability and security arose. Due to the sparse presence of real-world decentralized and infrastructureless systems, new protocols and applications have to be scrutinized by means of simulation, in (small-scale) testbeds, and by analytical models. In this paper, we discuss challenges of evaluating security mechanisms for mobile ad hoc networks and peer-to-peer systems. We focus on harmonizing predictions of analytical models and results obtained from simulation studies and testbed experiments.     

Reducing Protocol Analysis with XOR to the XOR-Free Case in the Horn Theory Based Approach

In the Horn theory based approach for cryptographic protocol analysis, cryptographic protocols and (Dolev?CYao) intruders are modeled by Horn theories and security analysis boils down to solving the derivation problem for Horn theories. This approach and the tools based on this approach, including ProVerif, have been very successful in the automatic analysis of cryptographic protocols. However, dealing with the algebraic properties of operators, such as the exclusive OR (XOR), which are frequently used in cryptographic protocols has been problematic. In particular, ProVerif cannot deal with XOR. In this paper, we show how to reduce the derivation problem for Horn theories with XOR to the XOR-free case. Our reduction works for an expressive class of Horn theories. A large class of intruder capabilities and protocols that employ the XOR operator can be modeled by these theories. Our reduction allows us to carry out protocol analysis using tools, such as ProVerif, that cannot deal with XOR, but are very efficient in the XOR-free case. We implemented our reduction and, in combination with ProVerif, used it for the fully automatic analysis of several protocols that employ the XOR operator. Among others, our analysis revealed a new attack on an IBM security module.     

Prological Language Processing

We describe a Prolog-based approach to the development of language processors (such as preprocessors, frontends, evaluators, tools for software modification and analysis). The design of the corresponding environment Laptob for prological language processing is outlined. Language processor definitions in Laptob are basically Prolog programs. The programs might contain grammars, that is, we consider logic grammars. The programs can be typed, and they can be higher-order. The adaptation and composition of the logic programs themselves is supported by meta-programming. The environment offers tool support for efficient scanning, testing, and application development based on a make-system. We report on recent and ongoing applications of the Prolog-based approach.     

Multigrid methods for discrete elliptic problems on triangular surfaces

We construct and analyze multigrid methods for discretized self-adjoint elliptic problems on triangular surfaces in ${\mathbb{R}^3}$ . The methods involve the same weights for restriction and prolongation as in the case of planar triangulations and therefore are easy to implement. We prove logarithmic bounds of the convergence rates with constants solely depending on the ellipticity, the smoothers and on the regularity of the triangles forming the triangular surface. Our theoretical results are illustrated by numerical computations.