Driven by the increasing demand for large-scale and high-performance data protection, disk-based de-duplication storage has become a new research focus of the storage industry and research community where several new ...
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ISBN:
(纸本)9781424464425
Driven by the increasing demand for large-scale and high-performance data protection, disk-based de-duplication storage has become a new research focus of the storage industry and research community where several new schemes have emerged recently. So far these systems are mainly inline de-duplication approaches, which are centralized and do not lend themselves easily to be extended to handle global de-duplication in a distributed environment. We present DEBAR, a de-duplication storage system designed to improve capacity, performance and scalability for de-duplication backup/archiving. DEBAR performs post-processing de-duplication, where backup streams are de-duplicated and cached on server-disks through an in-memory preliminary filter in phase I, and then completely de-duplicated in-batch in phase II. By decentralizing fingerprint lookup and update, DEBAR supports a cluster of servers to perform de-duplication backup in parallel, and is shown to scale linearly in both write throughput and physical capacity, achieving an aggregate throughput of 1.7GB/s and supporting a physical capacity of 2PB with 16 backup servers.
software Transactional Memory (STM) is a programming paradigm that allows a programmer to write parallel programs, without having to deal with the intricacies of synchronization. That burden is instead borne by the un...
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ISBN:
(纸本)9781424465330
software Transactional Memory (STM) is a programming paradigm that allows a programmer to write parallel programs, without having to deal with the intricacies of synchronization. That burden is instead borne by the underlying STM system. SwissTM is a lock-based STM, developed at EPFL, Switzerland. Memory locations map to entries in a lock table to detect conflicts. Increasing the number of locations that map to a lock reduces the number of locks to be acquired and improves throughput, while also increasing the possibility of false conflicts. False conflicts occur when a transaction that updates a location mapping to a lock, causes validation failure of another transaction, that reads a different location mapping to the same lock. In this paper, we present a solution for the false conflict problem and suggest an adaptive version of the same algorithm, to improve performance. Our algorithms produce significant throughput improvement in benchmarks with false conflicts.
Combining advance mathematic model to predict protein structure is one of the most challenging problems in structural biology. Condition Random Fields(CRF) is shown a powerful algorithm by many examples of informatics...
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Combining advance mathematic model to predict protein structure is one of the most challenging problems in structural biology. Condition Random Fields(CRF) is shown a powerful algorithm by many examples of informatics and widely used in protein structure predicted. CRFsampler can automatically optimizes more than ten thousand parameters quantifying the relationship among primary sequence and backbone angle; In this paper, we construct a parallel CRF protein sequence predicted model; by using backbone structure, the Cb is set up(GLY is pseudo), dihedral torsion angles are calculated. Between sequence and backbone angles, the parameters of feature is found by optimizing. The residue predicting accurate rate is 24.07%, the GLY predicting rate high to 64%. The rate is over 25% in the case of SAS>75%. The rate is also high when contact number small or larger.
How to design an efficient and cost effective software system is a million dollar question to every software engineer. The challenges lie in the fact that there is no such fixed rules and regulations, following which ...
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How to design an efficient and cost effective software system is a million dollar question to every software engineer. The challenges lie in the fact that there is no such fixed rules and regulations, following which will produce an efficient software system. Practitioners have proposed many solutions to address this issue. In this discussion, we will try to touch base on some of the vital points which a practitioner is encouraged to adapt in order to lead a team of software engineers to produce cost effective efficient system.
Behavior adaptation of software component is a crucial problem in component-based softwareengineering. A general approach is proposed to solve the behavior mismatch. Firstly, the synchronous vector between component ...
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Behavior adaptation of software component is a crucial problem in component-based softwareengineering. A general approach is proposed to solve the behavior mismatch. Firstly, the synchronous vector between component behaviors according to the abstract specification of component behavior is calculated, and the specification of the adaptor is given. Then, in order to detect automatically deadlock mismatch, the synchronous product of Symbolic Transition systems, which are the abstract specification of component behavior, is computed. The behavior of adaptor can be automatically calculated according to the synchronous vector. The adaptor can make component interaction correct. Finally, an example is presented to illustrate the proposed approach.
Thermal management is critical for clusters because of the increasing power consumption of modern processors, compact server architectures and growing server density in data centers. Thermal balancing mitigates hot sp...
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ISBN:
(纸本)9781424464425
Thermal management is critical for clusters because of the increasing power consumption of modern processors, compact server architectures and growing server density in data centers. Thermal balancing mitigates hot spots in a cluster through dynamic load distribution among servers. This paper presents two Control-theoretical Thermal Balancing (CTB) algorithms that dynamically balance the temperatures of different servers based on online measurements. CTB features controllers rigorously designed based on optimal control theory and a difference equation model that approximates the thermal dynamics of clusters. Control analysis and simulation results demonstrate that CTB achieves robust thermal balancing under a wide range of uncertainties: (1) when different tasks incur different power consumptions on the CPUs, (2) when servers experience different ambient temperatures, and (3) when servers experience thermal faults.
In this paper, we present a new heuristic that generates broadcast schemes in arbitrary networks. The heuristic gives optimal broadcast time for ring, tree and grid if the originator is on the corner. Extensive simula...
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In this paper, we present a new heuristic that generates broadcast schemes in arbitrary networks. The heuristic gives optimal broadcast time for ring, tree and grid if the originator is on the corner. Extensive simulations show that our new heuristic outperforms the best known broadcast algorithms for two different network models representing Internet and ATM networks. It also allows to generate broadcast time of networks of bigger size because its time complexity, O(|E|), is lower compared to the complexities of the other algorithms. The last advantage of the heuristic is that every node is informed via a shortest path from the originator.
The VF (voltage and frequency control) droop control techniques are used to set the VF reference value which allows the operation of multiple VSCs in parallel to share the loads and regulate system voltage and frequen...
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The VF (voltage and frequency control) droop control techniques are used to set the VF reference value which allows the operation of multiple VSCs in parallel to share the loads and regulate system voltage and frequency separately. In this paper, the characteristics of four VF control strategies which are: open loop VF control; VF control scheme with voltage feedback in abc reference frame; VF control scheme with voltage feedback in dq reference frame; VF control scheme with voltage and frequency feedback were presented.
The lag of parallel programming models and languages behind the advance of heterogeneous many-core processors has left a gap between the computational capability of modern systems and the ability of applications to ex...
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The lag of parallel programming models and languages behind the advance of heterogeneous many-core processors has left a gap between the computational capability of modern systems and the ability of applications to exploit them. Emerging programming models, such as CUDA and OpenCL, force developers to explicitly partition applications into components (kernels) and assign them to accelerators in order to utilize them effectively. An accelerator is a processor with a different ISA and micro-architecture than the main CPU. These static partitioning schemes are effective when targeting a system with only a single accelerator. However, they are not robust to changes in the number of accelerators or the performance characteristics of future generations of accelerators. In previous work, we presented the Harmony execution model for computing on heterogeneous systems with several CPUs and accelerators. In this paper, we extend Harmony to target systems with multiple accelerators using control speculation to expose parallelism. We refer to this technique as Kernel Level Speculation (KLS). We argue that dynamic parallelization techniques such as KLS are sufficient to scale applications across several accelerators based on the intuition that there will be fewer distinct accelerators than cores within each accelerator. In this paper, we use a complete prototype of the Harmony runtime that we developed to explore the design decisions and trade-offs in the implementation of KLS. We show that KLS improves parallelism to a sufficient degree while retaining a sequential programming model. We accomplish this by demonstrating good scaling of KLS on a highly heterogeneous system with three distinct accelerator types and ten processors.
Cloud computing is a way of computing, via the Internet, that broadly shares computer resources instead of using software or storage on a local PC. Cloud computing is an outgrowth of the ease-of-access to remote compu...
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Cloud computing is a way of computing, via the Internet, that broadly shares computer resources instead of using software or storage on a local PC. Cloud computing is an outgrowth of the ease-of-access to remote computing sites provided by the Internet. Instead of installing a suite of software for each computer, we'd only have to load one application. That application would allow workers to log into a Web-based service which hosts all the programs the user would need for his or her job. Remote machines owned by another company would run everything from e-mail to word processing to complex data analysis programs. It's called cloud computing, and it could change the entire computer industry. In a cloud computing system, there's a significant workload shift. Local computers no longer have to do all the heavy lifting when it comes to running applications. The network of computers that make up the cloud handles them instead. Hardware and software demands on the user's side decrease. The only thing the user's computer needs to be able to run is the cloud computing systems interface software, which can be as simple as a Web browser, and the cloud's network takes care of the rest.
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