Improving locality with dynamic memory allocation

Dynamic memory allocators are a determining factor of an application's performanceand have the opportunity to improve a major performance bottleneck ontoday's computer hardware: data locality. To approach this problem, a memoryallocator must rst oer strategies that allow the locality problem to be addressed.However, while focusing on locality, an allocator must also not ignore the existing constraintsof allocation speed and fragmentation, which further complicate its design. Inorder for a locality improving technique to be successfully employed in today's largecode applications, its integration needs to be automatic, without user intervention.The alternative, manual integration, is not a tractable solution.In this dissertation we develop three novel memory allocators that explore dierentallocation strategies that enhance an application's locality. We conduct the rststudy that shows that allocation speed, fragmentation and locality improving goalsare antagonistic. We develop an automatic method that supplies allocation hintsfrom C++ STL containers to their allocators. This method allows applications tobenet from locality improving techniques at the cost of a simple re-compilation. Weconduct the rst study that quanties the eect of allocation hints on performance,and show that an allocator with high locality of reference can be as competitive asone using an application's spatial feedback.To further allow dynamic memory allocation to improve an application's performance,new and non-traditional strategies need be explored. We develop a generic software tool that allows users to examine unconventional strategies. The tool allowsusers not only to focus on allocation strategies rather than their implementation, butalso to compare and contrast various approaches

Discutindo a educação ambiental no cotidiano escolar: desenvolvimento de projetos na escola formação inicial e continuada de professores

A presente pesquisa buscou discutir como a Educação Ambiental (EA) vem sendo trabalhada, no Ensino Fundamental e como os docentes desta escola compreendem e vem inserindo a EA no cotidiano escolar., em uma escola estadual do município de Tangará da Serra/MT, Brasil. Para tanto, realizou-se entrevistas com os professores que fazem parte de um projeto interdisciplinar de EA na escola pesquisada. Verificou-se que o projeto da escola não vem conseguindo alcançar os objetivos propostos por: desconhecimento do mesmo, pelos professores; formação deficiente dos professores, não entendimento da EA como processo de ensino-aprendizagem, falta de recursos didáticos, planejamento inadequado das atividades. A partir dessa constatação, procurou-se debater a impossibilidade de tratar do tema fora do trabalho interdisciplinar, bem como, e principalmente, a importância de um estudo mais aprofundado de EA, vinculando teoria e prática, tanto na formação docente, como em projetos escolares, a fim de fugir do tradicional vínculo “EA e ecologia, lixo e horta”.Facultad de Humanidades y Ciencias de la Educació

Custom Memory Allocation for Free Improving Data Locality with Container-Centric Memory Allocation

Abstract. We propose a novel container-centric memory allocation scheme. In this scheme, the container’s semantics guide the memory allocation, which results in data locality improvement and execution time reduction. The container-centric allocation provides the benefits of custom memory allocation, with the portability advantage. Applications need not change a single line of code, but rather change the underlying container library. Container-centric memory allocation increases data locality and reduces execution time, at no cost. At compile time, the container’s semantics provide knowledge which is evaluated at run-time, and then used for more efficient memory clustering. Our approach enables an application to use different allocation policies for different types of containers, or even different instantiations of the same type of container. We have integrated our memory allocator, named Defero, with the C++ Standard Template Library (STL) containers for automatic usage. We have used Defero in applications such as compiler infrastructure, molecular dynamics, network simulation, as well as on micro-kernels.

Architectural Support for Parallel Reductions in Scalable Shared-Memory Multiprocessors

Reductions are important and time-consuming operations in many scientific codes. Effective parallelization of reductions is a critical transformation for loop parallelization, especially for sparse, dynamic applications. Unfortunately, conventional reduction parallelization algorithms are not scalable. In this paper, we present new architectural support that significantly speeds-up parallel reduction and makes it scalable in shared-memory multiprocessors. The required architectural changes are mostly confined to the directory controllers. Experimental results based on simulations show that the proposed support is very effective. While conventional software-only reduction parallelization delivers average speedups of only 2.7 for 16 processors, our scheme delivers average speedups of 7.6.

STAPL: An adaptive, generic parallel C++ library

Abstract. The Standard Template Adaptive Parallel Library (STAPL) is a parallel library designed as a superset of the ANSI C++ Standard Template Library (STL). It is sequentially consistent for functions with the same name, and executes on uni- or multi-processor systems that utilize shared or distributed memory. STAPL is implemented using simple parallel extensions of C++ that currently provide a SPMD model of parallelism, and supports nested parallelism. The library is intended to be general purpose, but emphasizes irregular programs to allow the exploitation of parallelism in areas such as particle transport calculations, molecular dynamics, geometric modeling, and graph algorithms, which use dynamically linked data structures. STAPL provides several different algorithms for some library routines, and selects among them adaptively at run-time. STAPL can replace STL automatically by invoking a preprocessing translation phase. The performance of translated code is close to the results obtained using STAPL directly (less than 5 % performance deterioration). However, STAPL also provides functionality to allow the user to further optimize the code and achieve additional performance gains. We present results obtained using STAPL for a molecular dynamics code and a particle transport code.