Management Of Hardware Resources Research Articles

Cross-layer memory management for managed language applications

Performance and energy efficiency in memory have become critically important for a wide range of computing domains. However, it is difficult to control and optimize memory power and performance because these effects depend upon activity across multiple layers of the vertical execution stack. To address this challenge, we construct a novel and collaborative framework that employs object placement, cross-layer communication, and page-level management to effectively distribute application objects in the DRAM hardware to achieve desired power/performance goals. In this work, we describe the design and implementation of our framework, which is the first to integrate automatic object profiling and analysis at the application layer with fine-grained management of memory hardware resources in the operating system. We demonstrate the utility of our framework by employing it to more effectively control memory power consumption. We design a custom memory-intensive workload to show the potential of our approach. Next, we develop sampling and profiling-based analyses and modify the code generator in the HotSpot VM to understand object usage patterns and automatically determine and control the placement of hot and cold objects in a partitioned VM heap. This information is communicated to the operating system, which uses it to map the logical application pages to the appropriate DRAM ranks according to user-defined provisioning goals. We evaluate our framework and find that it achieves our test goal of significant DRAM energy savings across a variety of workloads, without any source code modifications or recompilations.

A New Approach for Dynamic Virtual Machine Consolidation in Cloud Data Centers

Cloud computing environments have introduced a new model of computing by shifting the location of computing infrastructure to the Internet network to reduce the cost associated with the management of hardware and software resources. The Cloud model uses virtualization technology to effectively consolidate virtual machines (VMs) into physical machines (PMs) to improve the utilization of PMs. Studies however have shown that the average utilization of PMs in many Cloud data centers is still lower than expected. The Cloud model is expected to improve the existing level of utilization by employing new approaches of consolidation mechanisms. In this paper we propose a new approach for dynamic consolidation of VMs in order to maximize the utilization of PMs. This is achieved by a dynamic programing algorithm that selects the best VMs for migration from an overloaded PM, considering the migration overhead of a VM. Evaluation results demonstrate that our algorithms achieve good performance.

SEATS: smart energy-aware task scheduling in real-time cloud computing

Mitigating energy consumption in Clouds reduces operational costs for providers. Power management policies which aim to reduce total energy consumed in data-centers pose challenges in both hardware technologies and resource management policies. We introduce an optimal utilization level of a host to execute a certain number of instructions to minimize energy consumption of the host. We also propose a virtual machine (VM) scheduling algorithm based on the unsurpassed utilization level to come up with optimal energy consumption while meeting a given QoS. In other words, our proposed algorithm regulates allocated computing resources of VMs on a host which results in reaching an optimal energy level in the host. The simulation results show that our proposed method not only reduces total energy consumption of a Cloud by 60 %, but also has a profound impact on turnaround times of real-time tasks by 94 %. It also increases the acceptance rate of arrival tasks by 96 %. Moreover, it takes a leading part in accepting lengthy tasks which have short deadlines.

High-Q Tunable Filters: Challenges and Potential

High-Q tunable filters are in demand in both wireless and satellite applications. The need for tunability and configurability in wireless systems arises when deploying different systems that coexist geographically. Such deployments take place regularly when an operator has already installed a network and needs to add a new-generation network, for example, to add a long-term evolution (LTE) network to an existing third-generation (3G) network. The availability of tunable/reconfigurable hardware will also provide the network operator the means for efficiently managing hardware resources, while accommodating multistandards requirements and achieving network traffic/capacity optimization. Wireless systems can also benefit from tunable filter technologies in other areas; for example, installing wireless infrastructure equipment, such as a remote radio unit (RRU) on top of a 15-story high communication tower, is a very costly task. By using tunable filters, one installation can serve many years since if there is a need to change the frequency or bandwidth, it can be done through remote electronic tuning, rather than installing a new filter. Additionally, in urban areas, there is a very limited space for wireless service providers to install their base stations due to expensive real estate and/or maximum weight loading constrains on certain installation locations such as light poles or power lines. Therefore, once an installation site is acquired, it is natural for wireless service providers to use tunable filters to pack many functions, such as multistandards and multibands, into one site.

Design of OpenCL framework for embedded multi-core processors

In modern mobile embedded systems, various energy-efficient hardware acceleration units are employed in addition to a multi-core CPU. To fully utilize the computational power in such heterogeneous systems, Open Computing Language (OpenCL) has been proposed. A key benefit of OpenCL is that it works on various computing platforms. However, most vendors offer OpenCL software development kits (SDKs) that support their own computing platforms. The study of the OpenCL framework for embedded multi-core CPUs is in a rudimentary stage. In this paper, an OpenCL framework for embedded multi-core CPUs that dynamically redistributes the time-varying workload to CPU cores in real time is proposed. A compilation environment for both host programs and OpenCL kernel programs was developed and OpenCL libraries were implemented. A performance evaluation was carried out with respect to various definitions of the device architecture and the execution model. When running on embedded multi-core CPUs, applications parallelized by OpenCL C showed much better performance than the applications written in C without parallelization. Furthermore, since programmers are capable of managing hardware resources and threads using OpenCL application programming interfaces (APIs) automatically, highly efficient computing both in terms of the performance and energy consumption on a heterogeneous computing platform can be easily achieved.

EFADS: Efficient, flexible and anonymous data sharing protocol for cloud computing with proxy re-encryption

The concept of cloud computing has emerged as the next generation of computing infrastructure to reduce the costs associated with the management of hardware and software resources. It is vital to its success that cloud computing is featured efficient, flexible and secure characteristics. In this paper, we propose an efficient and anonymous data sharing protocol with flexible sharing style, named EFADS, for outsourcing data onto the cloud. Through formal security analysis, we demonstrate that EFADS provides data confidentiality and data sharer's anonymity without requiring any fully-trusted party. From experimental results, we show that EFADS is more efficient than existing competing approaches. Furthermore, the proxy re-encryption scheme we propose in this paper may be independent of interests, i.e., compared to those previously reported proxy re-encryption schemes, the proposed scheme is the first pairing-free, anonymous and unidirectional proxy re-encryption scheme in the standard model.

Architecture Support for Domain-Specific Accelerator-Rich CMPs

This work discusses hardware architectural support for domain-specific accelerator-rich CMPs. First, we present a hardware resource management scheme for sharing of loosely coupled accelerators and arbitration of multiple requesting cores. Second, we present a mechanism for accelerator virtualization. This allows multiple accelerators to efficiently compose a larger virtual accelerator out of multiple smaller accelerators, as well as to collaborate as multiple copies of a simple accelerator. All of this work is supported by a fully automated simulation tool-chain for both accelerator generation and management. We present the applicability of our approach to four different application domains: medical imaging, commercial, computer vision, and navigation. Our results demonstrate large performance improvements and energy savings over a software implementation. We also show additional improvements that result from enhanced load balancing and simplification of the communication between the core and the arbitration mechanism.

Towards on Cloud Computing Standardization

Several computing paradigms have promised to deliver this computing vision, of which the latest one is known as Cloud computing. The term of cloud denotes the infrastructure as a “Cloud” from which businesses and users are able to access applications from anywhere in the world on demand. Cloud Computing is a new paradigm for the provision of computing infrastructure, and provides all the resources including networks, servers, storage, applications, and services as a service. This paradigm shifts the location of this infrastructure to the network to reduce the costs associated with the management of hard-ware and software resources. This paper intends to provide comprehensive review on Cloud computing in terms standardization in de jure standardization organizations such as ITU-T and JTC1, and de facto standardization organizations.

Design of General ATS Software Platform Based on Components

Generality is an important direction for Automatic Test System (ATS) ,while general software platform is the key technology to realize general ATS. Object-oriented programming design ideas and hierarchical and modular structure of the program have been adopted ,achieving the separation of data processing and testing processes; "Software backplane + Component" general software architecture has been used to achieve "the stability of the core layer, general, component layer configurable, scalable"; non-coding type of test program development way is used to achieve the development of test programs assembled . In order to make the hardware resource management centralized in the testing system, test resource management server is designed on the platform, which can put the hardware and software resources into service to achieve the equipments transferring. The results provide that the software platform can improve the development efficiency of test program and also maintenance costs are reduced.

Cascading Guided Search Cloud Service Search Engine

Cloud computing is one contemporary technology in which the research community has recently embarked. This paradigm shifts the location of the infrastructure to the network to reduce the costs associated with the management of hardware and software resources. Developers with innovative ideas for new Internet services no longer require the large capital outlays in hardware to deploy their service or the human expense to operate it. Organization adopts cloud computing services through service provider via Internet. In recent years, numbers of cloud service providers are increase. However, there is no study that focuses on search engine and web portal for cloud computing for users who want to find cloud service. At the same time, “vendor lock in” issues and the lack of common cloud standards delayed the interoperability across these providers. Thus, lead the cloud customer to face challenges and problems in selecting the right service provider who meets their needs. This research focus on meeting the user requeriment in cloud environment whereby, user requirements reflect to search query that entered by the end users and how these search queries are exactly matched with accurate cloud service. Therefore, end of the research cloud service search engine was developed as a proposed tool for meeting the user requirements.Â

ARM-Linux平台上移动机器人的传感器检测数据读取

使用嵌入式技术设计移动机器人控制器时，要求在Linux操作系统下管理硬件资源。故以移动机器人上配置的典型接近传感器为例，根据传感器的作用机理、硬件接口及ARM处理器的接口资源，设计了传感器的接口分配方案；并按照传感器的接口控制时序，使用交叉编译工具设计了红外、超声波传感器的字符设备驱动程序。测试结果表明，所设计的驱动程序对传感器测试数据的读取支持良好。 The controller design by making use of embedded technology for mobile robot requires managing hardware resources under Linux operating system. Taking the typical proximity sensors amounted on the board for example, considering work principle, sensors and hardware interface of sensors and interface resource of ARM-based microprocessor, an allocation scheme of interfaces is proposed for sensor controlling. Then, the character device drivers of the infrared and ultrasonic sensors are designed by using appropriate cross compiler tools according to the control timing sequences of interface of sensors. Test results show that measurement readings can be transferred correctly to the control system through device driver developed in this paper.

Operating System for Runtime Reconfigurable Multiprocessor Systems

Operating systems traditionally handle the task scheduling of one or more application instances on processor-like hardware architectures. RAMPSoC, a novel runtime adaptive multiprocessor System-on-Chip, exploits the dynamic reconfiguration on FPGAs to generate, start and terminate hardware and software tasks. The hardware tasks have to be transferred to the reconfigurable hardware via a configuration access port. The software tasks can be loaded into the local memory of the respective IP core either via the configuration access port or via the on-chip communication infrastructure (e.g. a Network-on-Chip). Recent-series of Xilinx FPGAs, such as Virtex-5, provide two Internal Configuration Access Ports, which cannot be accessed simultaneously. To prevent conflicts, the access to these ports as well as the hardware resource management needs to be controlled, e.g. by a special-purpose operating system running on an embedded processor. For that purpose and to handle the relations between temporally and spatially scheduled operations, the novel approach of an operating system is of high importance. This special purpose operating system, called CAP-OS (Configuration Access Port-Operating System), which will be presented in this paper, supports the clients using the configuration port with the services of priority-based access scheduling, hardware task mapping and resource management.

A Survey of Large Scale Data Management Approaches in Cloud Environments

In the last two decades, the continuous increase of computational power has produced an overwhelming flow of data. Moreover, the recent advances in Web technology has made it easy for any user to provide and consume content of any form. This has called for a paradigm shift in the computing architecture and large scale data processing mechanisms. Cloud computing is associated with a new paradigm for the provision of computing infrastructure. This paradigm shifts the location of this infrastructure to the network to reduce the costs associated with the management of hardware and software resources. This paper gives a comprehensive survey of numerous approaches and mechanisms of deploying data-intensive applications in the cloud which are gaining a lot of momentum in both research and industrial communities. We analyze the various design decisions of each approach and its suitability to support certain classes of applications and end-users. A discussion of some open issues and future challenges pertaining to scalability, consistency, economical processing of large scale data on the cloud is provided. We highlight the characteristics of the best candidate classes of applications that can be deployed in the cloud.

A High-Speed Dynamic Partial Reconfiguration Controller Using Direct Memory Access Through a Multiport Memory Controller and Overclocking with Active Feedback

Dynamically reconfigurable computing platforms provide promising methods for dynamic management of hardware resources, power, and performance. Yet, progress in dynamically reconfigurable computing is fundamentally limited by the reconfiguration time overhead. Prior research in the development of dynamic partial reconfiguration (DPR) controllers has been limited by its use of the Processor Local Bus (PLB). As a result, the bus was unavailable during DPR. This resulted in significant time overhead. To minimize the overhead, we introduce the use of a multiport memory controller (MPMC) that frees the PLB during the reconfiguration process. The processor is thus allowed to switch to other tasks during the reconfiguration operation. This effectively limits the reconfiguration overhead. An interrupt is used to inform the processor when the operation is complete. Therefore, the system can multitask during the reconfiguration operation. Furthermore, to maximize performance, we introduce the use of overclocking with active feedback. During overclocking, the use of active feedback is used to ensure that the device voltage and temperature are within nominal operating conditions. All of these contributions lead to significant performance improvements over current partial reconfiguration subsystems. The portability of the system, demonstrated on the Virtex-4 and the Virtex-5, consists of four different hardware platforms.

New Three-Level Resource Management Enhancing Quality of Offline Hardware Task Placement on FPGA

Currently, reconfigurable hardware devices feature a high density of heterogeneous resources to enable multitasking and offer flexibility in application needs. These concepts raise the need for efficient management of hardware tasks and hardware resources. The scheduling of hardware tasks is highly dependent on placement. Placement focuses on allocation of hardware resources required by the scheduled hardware tasks. In this paper, we propose novel three-level resource management that investigates enhancement of placement quality by reducing task rejection, configuration overheads, and by optimizing resource utilization. Improving placement quality will produce significant enhancement of performance for scheduling and overall execution time of the application in FPGA. Hence, the placement problem is formulated into a constrained optimization problem and resolved with powerful solvers using the Branch and Bound method. The obtained results of an application of heterogeneous hardware tasks show an average resource utilization of 36% of the available resources on the reconfigurable region and an overall overhead of 11% of total application running time, and we have eliminated the issue of task rejection. Compared to static implementation, the gain in resource utilization within the reconfigurable region achieves up to 43%.

Dynamic Multicore Resource Management: A Machine Learning Approach

A machine learning approach to multicore resource management produces self-optimizing on-chip hardware agents capable of learning, planning, and continuously adapting to changing workload demands. Machine learning is the study of computer programs and algorithms that learn about their environment and improve automatically with experience.This approach thus contrasts with today's predominant approach of directly specifying at design time how the hardware should accomplish the desired goal. This results in more efficient and flexible management of critical hardware resources at runtime.

ERP and SCM systems integration: The case of a valve manufacturer in China

Many modern organizations integrate enterprise resource planning (ERP) and supply chain management (SCM) systems, as they work in a complementary fashion. This often results in technical and organizational challenges. Neway, a Chinese organization, recently went through this complex process. This required efficient procurement and management of hardware, software, and human resources for successful completion. The integrated system was found to improve operations, foster a paperless environment, and provide efficient inventory tracking and picking. It also had several tangible benefits, including reduced lead time and improved inventory accuracy. ERP and SCM systems integration is still a novel concept for a Chinese manufacturing organization. Our case study details the organization's experience, identifies challenges that were faced, and describes solutions adopted to overcome them.

Software

Two principal themes are observed in software development, both aimed at improving the productivity of developing and maintaining new applications. The first is to provide increasingly rich system programming function in order to handle the details of managing hardware resources. The second is to provide application development facilities with logical structures and building blocks more closely aligned with the logic of the application itself. An additional challenge is to provide these in a way that will allow continued enhancement of existing software.