A2HA—automatic and adaptive host allocation in utility computing for bag-of-tasks

João Nuno Silva,Luís Veiga,Paulo Ferreira

doi:10.1007/s13174-011-0033-z

Abstract

AbstractThere are increasingly more computing problems requiring lengthy parallel computations. For those without access to current cluster or grid infrastructures, a recent and proven viable solution can be found with on-demand utility computing infrastructures, such as Amazon Elastic Compute Cloud (EC2). A relevant class of such problems, Bag-of-Tasks (BoT), can be easily deployed over such infrastructures (to run on pools of virtual computers), if provided with suitable software for host allocation. BoT problems are found in several and relevant scenarios such as image rendering and software testing.In BoT jobs, tasks are mostly independent; thus, they can run in parallel with no communication among them. The number of allocated hosts is relevant as it impacts both the speedup and the cost: if too many hosts are used, the speedup is high but this may not be cost-effective; if too few are used, the cost is low but speedup falls below expectations. For each BoT job, given that there is no prior knowledge of neither the total job processing time nor the time each task takes to complete, it is hard to determine the number of hosts to allocate. Current solutions (e.g., bin-packing algorithms) are not adequate as they require knowing in advance either the time that the next task will take to execute or, for higher efficiency, the time taken by each one of the tasks in each job considered.Thus, we present an algorithm and heuristics that adaptively predicts the number of hosts to be allocated, so that the maximum speedup can be obtained while respecting a given predefined budget. The algorithm and heuristics were simulated against real and theoretical workloads. With the proposed solution, it is possible to obtain speedups in line with the number of allocated hosts, while being charged less than the predefined budget.

Highlights

Grid and cluster infrastructures have become the epitome of computing/network architecture to address lengthy and heavy computational jobs
To evaluate the algorithm and the heuristics described in the previous section, we use three different representative examples of BoT jobs: (i) traces of a real image rendering job with 2,567 geometric objects, (ii) a synthetic job with a set of tasks whose processing times have a normal distribution, and (iii) the OutSystems software testing job
We present several results evaluating the effectiveness of the algorithm and heuristics previously described

Summary

Introduction

To take advantage of such an infrastructure, a user needs membership or institutional relationship with the organization, possibly virtual, controlling the computing resources. In this scenario, scientists or even home users lacking either the resources or the incentives (e.g., occasional needs) to take advantage of such infrastructures, are left without practical and viable options. Scientists or even home users lacking either the resources or the incentives (e.g., occasional needs) to take advantage of such infrastructures, are left without practical and viable options Another approach available to such users is provided by utility computing infrastructures such as Amazon Elastic Compute Cloud (EC2). They provide basic mechanisms and interfaces for users to create virtual computers. operating system, middleware, and job application code is left to

Objectives

Results

Conclusion