Performance Portability Strategies for Grid C++ Expression Templates

One of the key requirements for the Lattice QCD Application Development as part of the US Exascale Computing Project is performance portability across multiple architectures. Using the Grid C++ expression template as a starting point, we report on the progress made with regards to the Grid GPU offloading strategies. We present both the successes and issues encountered in using CUDA, OpenACC and Just-In-Time compilation. Experimentation and performance on GPUs with a SU(3)×SU(3) streaming test will be reported. We will also report on the challenges of using current OpenMP 4.x for GPU offloading in the same code.

Improved Elastic Model Matching Algorithm for Facial Expression Recognition

Key frames detected in Video stream contain sufficient expression information. In order to classify and recognize these expression information, a new elastic model matching algorithm is proposed in this paper. Firstly, expression template is transformed by Gabor wavelet , and the detection algorithm of the key expression in the template image is used. According to the feature information of the key expression, structure expression elastic graph, then by changing the key location in the expression template graph and doing non-rigid match of the expression template and expression elastic graph which is measured, so that similar degree between them is got. Finally, by improving the K-nearest neighbor classification strategy, the effective classification and recognition of measured image expression is achieved.

A New Vectorization Technique for Expression Templates in C++

Vector operations play an important role in high performance computing and are typically provided by highly optimized libraries that implement the Basic Linear Algebra Subprograms (BLAS) interface. In C++ templates and operator overloading allow the implementation of these vector operations as expression templates which construct custom loops at compile time and providing a more abstract interface. Unfortunately existing expression template libraries lack the performance of fast BLAS implementations. This paper presents a new approach - Statically Accelerated Loop Templates (SALT) - to close this performance gap by combining expression templates with an aggressive loop unrolling technique. Benchmarks were conducted using the Intel C++ compiler and GNU Compiler Collection to assess the performance of our library relative to Intel's Math Kernel Library as well as the Eigen template library. The results show that the approach is able to provide optimization comparable to the fastest available BLAS implementations, while retaining the convenience and flexibility of a template library.

Playa: High-Performance Programmable Linear Algebra

This paper introduces Playa, a high-level user interface layer for composing algorithms for complex multiphysics problems out of objects from other Trilinos packages. Among other features, Playa provides very high-performance overloaded operators implemented through an expression template mechanism. In this paper, we give an overview of the central Playa objects from a user's perspective, show application to a sequence of increasingly complex solver algorithms, provide timing results for Playa's overloaded operators and other functions, and briefly survey some of the implementation issues involved.