Communion: a new strategy form memory management in high-performance computer

Modern computers present a big gap between peak performance and sustained performance. There are many reasons for this situation, but mainly involving an inefficient usage of computational resources. Nowadays the memory system is the most critical component because of its growing inability to keep up with the processor requests. Technological trends have produced a large and growing gap between CPU speeds and DRAM speeds. Much research has focused this memory system problem, including program optimizing techniques, data locality enhancement, hardware and software prefetching, decoupled architectures, multithreading, speculative loads and execution. These techniques have got a relative success, but they focus only one component in the hardware or software systems. We present here a new strategy for memory management in high-performance computer systems, named COMMUNION. The basic idea behind this strategy is "cooperation". We introduce some interaction possibilities among system programs that are responsible to generate and execute application programs. So, we investigate two specific interactions: between the compiler and the operating system, and among the compiling system components. The experimental results show that it's possible to get improvements of about 10 times in execution time, and about 5 times in memory demand, enhancing the interaction between the compiling system components. In the interaction between compiler and operating system, named Compiler-Aided Page Replacement (CAPR), we achieved a reduction of about 10% in space-time product, with an increase of only 0.5% in the total execution time. All these results show that it s possible to manage main memory with a better efficiency than current systems.Facultad de Informátic

Evaluation of a local strategy for high performance memory management

Conventional operating systems, like Silicon Graphics' IRIX and IBM's AIX, adopt a single Memory Management algorithm. The choice of this algorithm is usually based on its good performance in relation to the set of programs executed in the computer. Some approximation of LRU (least­recently used) is usually adopted. This choice can take to certain situations in that the computer presents a bad performance due to its bad behavior for certain programs. A possible solution for such cases is to enable each program to have a specific Management algorithm (local strategy) that is adapted to its Memory access pattern. For example, programs with sequential access pattern, such as SOR, should be managed by the algorithm MRU (most­recently used) because its bad performance when managed by LRU. In this strategy it is very important to decide the Memory partitioning strategy among the programs in execution in a multiprogramming environment. Our strategy named CAPR (Compiler­Aided Page Replacement) analyze the pattern of Memory references from the source program of an application and communicate these characteristics to the operating system that will make the choice of the best Management algorithm and Memory partitioning strategy. This paper evaluates the influence of the Management algorithms and Memory partitioning strategy in the global system performance and in the individual performance of each program. It is also presented a comparison of this local strategy with the classic global strategy and the viability of the strategy is analyzed. The obtained results showed a difference of at least an order of magnitude in the number of page faults among the algorithms LRU and MRU in the global strategy. After that, starting from the analysis of the intrinsic behavior of each application in relation to its Memory access pattern and of the number of page faults, an optimization procedure of Memory system performance was developed for multiprogramming environments. This procedure allows to decide system performance parameters, such as Memory partitioning strategy among the programs and the appropriate Management algorithm for each program. The results showed that, with the local Management strategy, it was obtained a reduction of at least an order of magnitude in the number of page faults and a reduction in the mean Memory usage of about 3 to 4 times in relation to the global strategy. This performance improvement shows the viability of our strategy. It is also presented some implementation aspects of this strategy in traditional operating systems.Sistemas Distribuidos - Redes ConcurrenciaRed de Universidades con Carreras en Informática (RedUNCI

Communion: a new strategy form memory management in high-performance computer

Modern computers present a big gap between peak performance and sustained performance. There are many reasons for this situation, but mainly involving an inefficient usage of computational resources. Nowadays the memory system is the most critical component because of its growing inability to keep up with the processor requests. Technological trends have produced a large and growing gap between CPU speeds and DRAM speeds. Much research has focused this memory system problem, including program optimizing techniques, data locality enhancement, hardware and software prefetching, decoupled architectures, multithreading, speculative loads and execution. These techniques have got a relative success, but they focus only one component in the hardware or software systems. We present here a new strategy for memory management in high-performance computer systems, named COMMUNION. The basic idea behind this strategy is "cooperation". We introduce some interaction possibilities among system programs that are responsible to generate and execute application programs. So, we investigate two specific interactions: between the compiler and the operating system, and among the compiling system components. The experimental results show that it's possible to get improvements of about 10 times in execution time, and about 5 times in memory demand, enhancing the interaction between the compiling system components. In the interaction between compiler and operating system, named Compiler-Aided Page Replacement (CAPR), we achieved a reduction of about 10% in space-time product, with an increase of only 0.5% in the total execution time. All these results show that it s possible to manage main memory with a better efficiency than current systems.Facultad de Informátic

Evaluation of a local strategy for high performance memory management

Conventional operating systems, like Silicon Graphics' IRIX and IBM's AIX, adopt a single Memory Management algorithm. The choice of this algorithm is usually based on its good performance in relation to the set of programs executed in the computer. Some approximation of LRU (least­recently used) is usually adopted. This choice can take to certain situations in that the computer presents a bad performance due to its bad behavior for certain programs. A possible solution for such cases is to enable each program to have a specific Management algorithm (local strategy) that is adapted to its Memory access pattern. For example, programs with sequential access pattern, such as SOR, should be managed by the algorithm MRU (most­recently used) because its bad performance when managed by LRU. In this strategy it is very important to decide the Memory partitioning strategy among the programs in execution in a multiprogramming environment. Our strategy named CAPR (Compiler­Aided Page Replacement) analyze the pattern of Memory references from the source program of an application and communicate these characteristics to the operating system that will make the choice of the best Management algorithm and Memory partitioning strategy. This paper evaluates the influence of the Management algorithms and Memory partitioning strategy in the global system performance and in the individual performance of each program. It is also presented a comparison of this local strategy with the classic global strategy and the viability of the strategy is analyzed. The obtained results showed a difference of at least an order of magnitude in the number of page faults among the algorithms LRU and MRU in the global strategy. After that, starting from the analysis of the intrinsic behavior of each application in relation to its Memory access pattern and of the number of page faults, an optimization procedure of Memory system performance was developed for multiprogramming environments. This procedure allows to decide system performance parameters, such as Memory partitioning strategy among the programs and the appropriate Management algorithm for each program. The results showed that, with the local Management strategy, it was obtained a reduction of at least an order of magnitude in the number of page faults and a reduction in the mean Memory usage of about 3 to 4 times in relation to the global strategy. This performance improvement shows the viability of our strategy. It is also presented some implementation aspects of this strategy in traditional operating systems.Sistemas Distribuidos - Redes ConcurrenciaRed de Universidades con Carreras en Informática (RedUNCI

Caracterização de Cargas de Trabalho em Estudos sobre Gerência de Memória Virtual

Abstract. The characterization of workloads for memory systems evaluation is important because it allows to detect factors in programs which may or may not favor the performance of each possible system configuration. This paper describes the Elephantools: a software tools package applied to the characterization of workloads used in experiments on virtual memory management. Providing visual and statistics resources for identifying memory access patterns inherent in specific programs, the Elephantools contributes both to the enrichment of studies on reference locality and to the understanding of some phenomena observed in simulations. Resumo. A caracterização de cargas de trabalho utilizadas em avaliações de sistemas de memória é importante porque permite detectar fatores presentes nos programas que favorecem ou não o desempenho de cada possível configuração do sistema. Este artigo descreve o Elephantools: um pacote composto por ferramentas de software voltadas à caracterização de cargas de trabalho em experimentos sobre gerência de memória virtual. Oferecend

Performance Analysis Method for Robotic Process Automation

Recent studies show that decision making in Business Process Management (BPM) and incorporating sustainability in business is vital for service innovation within a company. Likewise, it is also possible to save time and money in an automated, intelligent and sustainable way. Robotic Process Automation (RPA) is one solution that can help businesses improve their BPM and sustainability practices through digital transformation. However, deciding which processes to automate with RPA technology can be complex. Consequently, this paper presents a model for selecting indicators to determine the profitability of shifting to RPA in selected business processes. The method used in this work is the Performance Analysis Method, which allows for predicting which processes could be replaced by RPA to save time and money in a service workflow. The Performance Analysis Method consists of collecting data on the speed and efficiency of a business process and then using that data to develop discrete event simulations to estimate the cost of automating parts of that process. A case study using this model is presented, using business process data from an international utility company as input to the discrete event simulation. The model used in this study predicts that this Electric Utility Company (EUC) will save a substantial amount of money if it implements RPA in its call center