Achieving Dynamic Workload Balancing for P2P Volunteer Computing

2015 ◽  
Author(s):  
Wei Li ◽  
William Guo ◽  
Eugenie Franzinelli
Keyword(s):  
Volunteer Computing ◽  
Workload Balancing

scholarly journals GPrimer: a fast GPU-based pipeline for primer design for qPCR experiments

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jeongmin Bae ◽  
Hajin Jeon ◽  
Min-Soo Kim
Keyword(s):  
Data Structures ◽  
Primer Design ◽  
Main Memory ◽  
Design Tools ◽  
Workload Balancing ◽  
Qpcr Analysis ◽  
Computational Speed ◽  
Entire Sequence ◽  
Target Sequences ◽  
Coalesced Memory

Abstract Background Design of valid high-quality primers is essential for qPCR experiments. MRPrimer is a powerful pipeline based on MapReduce that combines both primer design for target sequences and homology tests on off-target sequences. It takes an entire sequence DB as input and returns all feasible and valid primer pairs existing in the DB. Due to the effectiveness of primers designed by MRPrimer in qPCR analysis, it has been widely used for developing many online design tools and building primer databases. However, the computational speed of MRPrimer is too slow to deal with the sizes of sequence DBs growing exponentially and thus must be improved. Results We develop a fast GPU-based pipeline for primer design (GPrimer) that takes the same input and returns the same output with MRPrimer. MRPrimer consists of a total of seven MapReduce steps, among which two steps are very time-consuming. GPrimer significantly improves the speed of those two steps by exploiting the computational power of GPUs. In particular, it designs data structures for coalesced memory access in GPU and workload balancing among GPU threads and copies the data structures between main memory and GPU memory in a streaming fashion. For human RefSeq DB, GPrimer achieves a speedup of 57 times for the entire steps and a speedup of 557 times for the most time-consuming step using a single machine of 4 GPUs, compared with MRPrimer running on a cluster of six machines. Conclusions We propose a GPU-based pipeline for primer design that takes an entire sequence DB as input and returns all feasible and valid primer pairs existing in the DB at once without an additional step using BLAST-like tools. The software is available at https://github.com/qhtjrmin/GPrimer.git.

scholarly journals Dynamic Scheduling Algorithm in Cyber Mimic Defense Architecture of Volunteer Computing

2021 ◽  
Vol 21 (3) ◽  
pp. 1-33
Author(s):  
Qianmu Li ◽  
Shunmei Meng ◽  
Xiaonan Sang ◽  
Hanrui Zhang ◽  
Shoujin Wang ◽  
...  
Keyword(s):  
Dynamic Scheduling ◽  
Scheduling Algorithm ◽  
Dynamic Change ◽  
High Energy ◽  
Transformation Rule ◽  
Volunteer Computing ◽  
Attack Behavior ◽  
Time Threshold ◽  
Security And Reliability ◽  
Multi Level

Volunteer computing uses computers volunteered by the general public to do distributed scientific computing. Volunteer computing is being used in high-energy physics, molecular biology, medicine, astrophysics, climate study, and other areas. These projects have attained unprecedented computing power. However, with the development of information technology, the traditional defense system cannot deal with the unknown security problems of volunteer computing . At the same time, Cyber Mimic Defense (CMD) can defend the unknown attack behavior through its three characteristics: dynamic, heterogeneous, and redundant. As an important part of the CMD, the dynamic scheduling algorithm realizes the dynamic change of the service centralized executor, which can enusre the security and reliability of CMD of volunteer computing . Aiming at the problems of passive scheduling and large scheduling granularity existing in the existing scheduling algorithms, this article first proposes a scheduling algorithm based on time threshold and task threshold and realizes the dynamic randomness of mimic defense from two different dimensions; finally, combining time threshold and random threshold, a dynamic scheduling algorithm based on multi-level queue is proposed. The experiment shows that the dynamic scheduling algorithm based on multi-level queue can take both security and reliability into account, has better dynamic heterogeneous redundancy characteristics, and can effectively prevent the transformation rule of heterogeneous executors from being mastered by attackers.

scholarly journals An Incentive-based Mechanism for Volunteer Computing Using Blockchain

2021 ◽  
Vol 21 (4) ◽  
pp. 1-22
Author(s):  
Ismaeel Al Ridhawi ◽  
Moayad Aloqaily ◽  
Yaser Jararweh
Keyword(s):  
Resource Sharing ◽  
Secure Communication ◽  
Service Providers ◽  
Volunteer Computing ◽  
Resource Usage ◽  
Content Filtering ◽  
Computing Device ◽  
Blockchain Technology ◽  
Smart Agriculture ◽  
Industrial Solutions

The rise of fast communication media both at the core and at the edge has resulted in unprecedented numbers of sophisticated and intelligent wireless IoT devices. Tactile Internet has enabled the interaction between humans and machines within their environment to achieve revolutionized solutions both on the move and in real-time. Many applications such as intelligent autonomous self-driving, smart agriculture and industrial solutions, and self-learning multimedia content filtering and sharing have become attainable through cooperative, distributed, and decentralized systems, namely, volunteer computing. This article introduces a blockchain-enabled resource sharing and service composition solution through volunteer computing. Device resource, computing, and intelligence capabilities are advertised in the environment to be made discoverable and available for sharing with the aid of blockchain technology. Incentives in the form of on-demand service availability are given to resource and service providers to ensure fair and balanced cooperative resource usage. Blockchains are formed whenever a service request is initiated with the aid of fog and mobile edge computing (MEC) devices to ensure secure communication and service delivery for the participants. Using both volunteer computing techniques and tactile internet architectures, we devise a fast and reliable service provisioning framework that relies on a reinforcement learning technique. Simulation results show that the proposed solution can achieve high reward distribution, increased number of blockchain formations, reduced delays, and balanced resource usage among participants, under the premise of high IoT device availability.

scholarly journals Pulsar Discovery by Global Volunteer Computing: Fig. 1

Science ◽  
2010 ◽  
Vol 329 (5997) ◽  
pp. 1305-1305 ◽  
Author(s):  
B. Knispel ◽  
B. Allen ◽  
J. M. Cordes ◽  
J. S. Deneva ◽  
D. Anderson ◽  
...  
Keyword(s):  
Survey Data ◽  
Large Data ◽  
Large Data Sets ◽  
Volunteer Computing ◽  
Data Sets ◽  
Pulse Profile ◽  
Computing Power ◽  
Spin Period ◽  
Arecibo Observatory ◽  
Computer Power

Einstein@Home aggregates the computer power of hundreds of thousands of volunteers from 192 countries to mine large data sets. It has now found a 40.8-hertz isolated pulsar in radio survey data from the Arecibo Observatory taken in February 2007. Additional timing observations indicate that this pulsar is likely a disrupted recycled pulsar. PSR J2007+2722’s pulse profile is remarkably wide with emission over almost the entire spin period; the pulsar likely has closely aligned magnetic and spin axes. The massive computing power provided by volunteers should enable many more such discoveries.

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