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Prediction of CPU idle-busy activity pattern

Qian Diao, Justin Song
2008 High-Performance Computer Architecture  
We evaluate this model with idle traces collected on dual-core and quad-core processor, and find this method can well predict CPU's activity pattern at the error level not exceeding 4%.  ...  CPU C-states can be used to reduce power consumption during processor idle time. The key unsolved problem is: when and how to use which Cstate.  ...  Summary In this paper, we define CPU activity pattern in terms of core idle or busy status, and also use a statistical model based method for CPU activity pattern prediction.  ... 
doi:10.1109/hpca.2008.4658625 dblp:conf/hpca/DiaoS08 fatcat:3g6oz4terbe53prpkencymg4cu

Performance Estimation for Scheduling on Shared Networks [chapter]

Jaspal Subhlok, Shreenivasa Venkataramaiah
2003 Lecture Notes in Computer Science  
For sharing of a single computation node or network link, the actual performance is predicted, while for sharing of multiple nodes and links, performance bounds are developed.  ...  This paper develops a framework to model the performance of parallel applications executing in a shared network computing environment.  ...  (W-7405-ENG-36) between the DOE and the Regents of the University of California.  ... 
doi:10.1007/10968987_8 fatcat:xrs5z3adnbhkhicbmybw4dodma

POSSE: Patterns of Systems During Software Encryption [article]

David Noever, Samantha Miller Noever
2021 arXiv   pre-print
A common goal of this behavioral detector seeks to anticipate and short-circuit the final step of hard-drive locking with encryption and the demand for payment to return the file system to its baseline  ...  All algorithms classified the 3 possible classes (idle, encryption, and compression) with greater than 91% accuracy.  ...  Figure 1 . 1 Pattern of Hardware Sensors to Predict Activity Figure 2 . 2 Activity Spikes Alternating Idle and Encryption Steps Figure 3 . 3 Encryption Cycles and Overlay for Hardware Figure 4 .  ... 
arXiv:2109.12162v1 fatcat:sqrbozz6rrcvffhezaiqjzjyoi

Energy Prediction for Cloud Workload Patterns [chapter]

Ibrahim Alzamil, Karim Djemame
2017 Lecture Notes in Computer Science  
, and up to -4.47 MPE for the VM energy prediction based on periodic workload pattern.  ...  This framework first predicts the VMs' workload based on historical workload patterns using Autoregressive Integrated Moving Average (ARIMA) model.  ...  The idle energy is consumed when the PM is turned on but not running any workload. The active energy is the extra energy added to the idle when the PM is busy and running some workload.  ... 
doi:10.1007/978-3-319-61920-0_12 fatcat:lwbgbpnzx5evhlsxzommq5hszy

Monitoring system activity for OS-directed dynamic power management

Luca Benini, Alessandro Bogliolo, Stefano Cavallucci, Bruno Riccó
1998 Proceedings of the 1998 international symposium on Low power electronics and design - ISLPED '98  
We used our monitoring tool to collect data on the usage of system resources disks, CPU, keyboard and mouse for a laptop computer, under several workload conditions.  ...  Our monitoring system is minimally intrusive, and has negligible impact on system activity. Moreover, it can be used both for on-line system monitoring and o -line data collection.  ...  Detecting the scheduling of the idle process is a simple way to monitor activity and idleness of the CPU.  ... 
doi:10.1145/280756.280887 dblp:conf/islped/BeniniBCR98 fatcat:4lytl5ytqnaenci2n542eziaga

Smartphone Energy Drain in the Wild

Xiaomeng Chen, Ning Ding, Abhilash Jindal, Y. Charlie Hu, Maruti Gupta, Rath Vannithamby
2015 Performance Evaluation Review  
Second, through analyzing traces collected on 1520 Galaxy S3 and S4 devices in the wild, we present detailed analysis of where the CPU time and energy is spent across the 1520 devices, inside the 800 apps  ...  The limited battery life of modern smartphones remains a leading factor adversely affecting the mobile experience of millions of smartphone users.  ...  (2) There are no networking activities during CPU idle while there can be networking activities during CPU busy which adds to the energy drain during CPU busy. Energy breakdown by components.  ... 
doi:10.1145/2796314.2745875 fatcat:tsd3awp6pratdjb4chi7b4cem4

A Novel Power Management for CMP Systems in Data-Intensive Environment

Pengju Shang, Jun Wang
2011 2011 IEEE International Parallel & Distributed Processing Symposium  
Only scaling down the processor's frequency based on its busy/idle ratio cannot fully exploit opportunities of saving power.  ...  Our experiments show that besides the busy and idle status, each processor may also have I/O wait phases waiting for I/O operations to complete.  ...  This work is supported in part by the US National Science Foundation grant CCF-0811413, US Department of Energy Early Career Principal Investigator Award DE-FG02-07ER25747, and National Science Foundation  ... 
doi:10.1109/ipdps.2011.19 dblp:conf/ipps/ShangW11 fatcat:dy4vg6jfpvg5lngehlzwhsv7im

Resource use pattern analysis for predicting resource availability in opportunistic grids

Marcelo Finger, Germano C. Bezerra, Danilo R. Conde
2009 Concurrency and Computation  
This prediction method is based on the assumption of the existence of several classes of computational resource use patterns, which can be used to predict resource availability.  ...  This work presents a method for predicting resource availability in opportunistic grids by means of Use Pattern Analysis (UPA), a technique based on non-supervised learning methods.  ...  the first period of activation.  ... 
doi:10.1002/cpe.1478 fatcat:ha3ibf6ei5dlfjpypp3u4wzz2y

Instant-Access Cycle-Stealing for Parallel Applications Requiring Interactive Response [chapter]

P. H. J. Kelly, S. Pelagatti, M. Rossiter
2002 Lecture Notes in Computer Science  
In this paper we study the use of idle cycles in a network of desktop workstations under unfavourable conditions: we aim to use idle cycles to improve the responsiveness of interactive applications through  ...  We therefore assume a high level of primary activity by the desktop workstations' users, and aim to keep interference with their work within reasonable limits.  ...  Traces were collected during the busy daytime hours, weekdays 9am to 6pm. Pattern of workstation utilisation Of all the one-second samples, 86% were idle. Idle periods occur very frequently.  ... 
doi:10.1007/3-540-45706-2_122 fatcat:qsjfdp37ojh4nd3bzbja2w52ve

Energy-aware cost prediction and pricing of virtual machines in cloud computing environments

Mohammad Aldossary, Karim Djemame, Ibrahim Alzamil, Alexandros Kostopoulos, Antonis Dimakis, Eleni Agiatzidou
2019 Future generations computer systems  
accuracy for various Cloud application workload patterns.  ...  The evaluation on a Cloud testbed show that the proposed energy-aware cost prediction framework is capable of predicting the workload, power consumption and estimating total cost of the VMs with good prediction  ...  matched the pattern of the predicted VMs CPU utilisation, as shown in Figures 19 and 21 .  ... 
doi:10.1016/j.future.2018.10.027 fatcat:ps34ostxtjeghkals42nuqthym

Comparing algorithm for dynamic speed-setting of a low-power CPU

Kinshuk Govil, Edwin Chan, Hal Wasserman
1995 Proceedings of the 1st annual international conference on Mobile computing and networking - MobiCom '95  
Weiser et al. and others have suggested that this may be accomplished by a CPU which dynamically changes speed and voltage, thereby saving energy by spreading run cycles into idle time.  ...  Our work clarifies a fundamental power vs. delay tradeoff, as well as the role of prediction and of smoothing in dynamic speed-setting policies.  ...  -Speed-setting: If the prediction is for a Since busy interval, PAST increases speed; if for a mostly idle interval, PAST decreases speed.  ... 
doi:10.1145/215530.215546 dblp:conf/mobicom/GovilCW95 fatcat:75r54cl7wfgbtc3oiyvkdexsqq

A Dynamic Power Management Controller for Optimizing Servers' Energy Consumption in Service Centers [chapter]

Tudor Cioara, Ioan Salomie, Ionut Anghel, Iulian Chira, Alexandru Cocian, Ealan Henis, Ronen Kat
2011 Lecture Notes in Computer Science  
We propose techniques for identifying the over-provisioned resources and putting them into low-power states until there is a prediction for a workload requiring scaling-up the server's computing capacity  ...  Virtualization techniques are used for a uniform and dependence free management of server tasks.  ...  period prediction engine Knowledge Base HDD Correlation Engine CPU Fuzzy controller VM HDD Idle period prediction engine Knowledge Base CPU Fuzzy controller HDD Idle period prediction  ... 
doi:10.1007/978-3-642-19394-1_17 fatcat:lpopzicjzjckhglvodfzarwbde

Multi-state grid resource availability characterization

Brent Rood, Michael J. Lewis
2007 2007 8th IEEE/ACM International Conference on Grid Computing  
Since grid applications also vary as to how well they tolerate the failure of the host on which they run, grid schedulers must begin to predict and consider how resources will transition between availability  ...  A simple predictor based on the previous day's behavior indicates that the states and categories are somewhat predictable, thereby supporting the potential usefulness of multi-state grid resource availability  ...  The trace consists of time-stamped CPU load (as a percentage) and idle time (in seconds).  ... 
doi:10.1109/grid.2007.4354114 dblp:conf/grid/RoodL07 fatcat:fi5emmkc6jbolgtniauqwukgiq

An Idle Compute Cycle Prediction Service for Computational Grids [chapter]

Suntae Hwang, Eun-Jin Im, Karpjoo Jeong, Hyoungwoo Park
2004 Lecture Notes in Computer Science  
In this paper, we argue PCs at university computer labs have a great potential for the utilization of idle CPU cycles, and propose two techniques for predicting idle cycles of those PCs: heuristic and  ...  idleness prediction techniques.  ...  In this model, we simply assume that idle-ness patterns are repeated in a weekly basis. That is, we predict the idle-ness patterns of the current week based on those of the previous two weeks.  ... 
doi:10.1007/978-3-540-24685-5_15 fatcat:bjp4b5hzxjfqrievvnw5nthlpy

Understanding idle behavior and power gating mechanisms in the context of modern benchmarks on CPU-GPU Integrated systems

Manish Arora, Srilatha Manne, Indrani Paul, Nuwan Jayasena, Dean M. Tullsen
2015 2015 IEEE 21st International Symposium on High Performance Computer Architecture (HPCA)  
This paper presents a comprehensive analysis of idleness behavior of modern CPU workloads, consisting of both consumer and CPU-GPU benchmarks.  ...  As CPUs become tightly integrated with GPUs and other accelerators, the incidence of short duration idle events are becoming increasingly common.  ...  These are crafted, in large part, to evaluate the active behavior of the CPU; in that context, CPU idleness is uninteresting.  ... 
doi:10.1109/hpca.2015.7056047 dblp:conf/hpca/AroraMPJT15 fatcat:3glzawrv2fh3dpaba44bhgxrum
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