Dwarfs on Accelerators: Enhancing OpenCL Benchmarking for Heterogeneous Computing Architectures

For reasons of both performance and energy efficiency, high-performance computing (HPC) hardware is becoming increasingly heterogeneous. The OpenCL framework supports portable programming across a wide range of computing devices and is gaining influence in programming next-generation accelerators. To characterize the performance of these devices across a range of applications requires a diverse, portable and configurable benchmark suite, and OpenCL is an attractive programming model for this purpose. We present an extended and enhanced version of the OpenDwarfs OpenCL benchmark suite, with a strong focus placed on the robustness of applications, curation of additional benchmarks with an increased emphasis on correctness of results and choice of problem size. Preliminary results and analysis are reported for eight benchmark codes on a diverse set of architectures -- three Intel CPUs, five Nvidia GPUs, six AMD GPUs and a Xeon Phi.Comment: 10 pages, 5 figure

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

A Tool for Analyzing Performance of Memory Allocators in Linux

Tato diplomová práce prezentuje nástroj, který umožňuje analýzu vlastností dynamických paměťových alokátorů se zaměřením na jejich výkon. Práce identifikuje důležité výkonnostní metriky paměťových alokátorů a také faktory prostředí a programu, které tyto metriky mohou ovlivnit. Na základě těchto nalezených metrik byl navrhnut a implementován nástroj, který umožnuje jejich sběr a analýzu. Nástroj umožňuje tvorbu různých scénářů použití alokátorů tak, aby bylo možné analyzovat chování alokátorů za různých podmínek. Tento nástroj byl testován na několika dostupných paměťových alokátorech se svobodnou licencí.This diploma thesis presents a tool for dynamic memory allocator analysis, focused on their performance. The work identifies the important memory allocator performance metrics, as well as the environment and program factors influencing these metrics. Using this knowledge, a tool was designed and implemented. This tool allows to gather and analyze these metrics. The tool provides the ability to create memory allocator usage scenarios for the purpose of the allocator behavior analysis under different conditions. The tool was tested on several available memory allocators with free license.