48 research outputs found

    A dynamic power-aware partitioner with task migration for multicore embedded systems

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    Nowadays, a key design issue in embedded systems is how to reduce the power consumption, since batteries have a limited energy budget. For this purpose, several techniques such as Dynamic Voltage Scaling (DVS) or task migration can be used. DVS allows reducing power by selecting the optimal voltage supply, while task migration achieves this effect by balancing the workload among cores. This paper first analyzes the impact on energy due to task migration in multicore embedded systems with DVS capability and using the well-known Worst Fit (WF) partitioning heuristic. To reduce overhead, migrations are only performed at the time that a task arrives to and/or leaves the system and, in such a case, only one migration is allowed. The huge potential on energy saving due to task migration, leads us to propose a new dynamic partitioner, namely DP, that migrates tasks in a more efficient way than typical partitioners. Unlike WF, the proposed algorithm examines which is the optimal target core before allowing a migration. Experimental results show that DP can improve energy consumption in a factor up to 2.74 over the typical WF algorithm. © 2011 Springer-Verlag.This work was supported by Spanish CICYT under Grant TIN2009-14475-C04-01, and by Consolider-Ingenio under Grant CSD2006-00046.March Cabrelles, JL.; Sahuquillo Borrás, J.; Petit Martí, SV.; Hassan Mohamed, H.; Duato Marín, JF. (2011). A dynamic power-aware partitioner with task migration for multicore embedded systems. En Euro-Par 2011 Parallel Processing. Springer Verlag (Germany). 2011(6852):218-229. https://doi.org/10.1007/978-3-642-23400-2_21S21822920116852AlEnawy, T.A., Aydin, H.: Energy-Aware Task Allocation for Rate Monotonic Scheduling. In: Proceedings of the 11th Real Time on Embedded Technology and Applications Symposium, March 7-10, pp. 213–223. IEEE Computer Society, San Francisco (2005)Aydin, H., Yang, Q.: Energy-Aware Partitioning for Multiprocessor Real-Time Systems. In: Proceedings of the 17th International Parallel and Distributed Processing Symposium, Workshop on Parallel and Distributed Real-Time Systems, April 22-26, p. 113. IEEE Computer Society, Nice (2003)Baker, T.P.: An Analysis of EDF schedulability on a multiprocessor. IEEE Transactions on Parallel and Distributed Systems 16(8), 760–768 (2005)Brandenburg, B.B., Calandrino, J.M., Anderson, J.H.: On the Scalability of Real-Time Scheduling Algorithms on Multicore Platforms: A Case Study. In: Proceedings of the 29th Real-Time Systems Symposium, November 30-December 3, pp. 157–169. IEEE Computer Society, Barcelona (2008)Brião, E., Barcelos, D., Wronski, F., Wagner, F.R.: Impact of Task Migration in NoC-based MPSoCs for Soft Real-time Applications. In: Proceedings of the International Conference on VLSI, October 15-17, pp. 296–299. IEEE Computer Society, Atlanta (2007)Cazorla, F., Knijnenburg, P., Sakellariou, R., Fernández, E., Ramirez, A., Valero, M.: Predictable Performance in SMT Processors: Synergy between the OS and SMTs. IEEE Transactions on Computers 55(7), 785–799 (2006)Donald, J., Martonosi, M.: Techniques for Multicore Thermal Management: Classification and New Exploration. In: Proceedings of the 33rd Annual International Symposium on Computer Architecture, June 17-21, pp. 78–88. IEEE Computer Society, Boston (2006)El-Haj-Mahmoud, A., AL-Zawawi, A., Anantaraman, A., Rotenberg, E.: Virtual Multiprocessor: An Analyzable, High-Performance Architecture for Real-Time Computing. In: Proceedings of the International Conference on Compilers, Architectures and Synthesis for Embedded Systems, September 24-27, pp. 213–224. ACM Press, San Francisco (2005)Hung, C., Chen, J., Kuo, T.: Energy-Efficient Real-Time Task Scheduling for a DVS System with a Non-DVS Processing Element. In: Proceedings of the 27th Real-Time Systems Symposium, December 5-8, pp. 303–312. IEEE Computer Society, Rio de Janeiro (2006)Kalla, R., Sinharoy, B., Tendler, J.M.: IBM Power5 Chip: A Dual-Core Multithreaded Processor. IEEE Micro 24(2), 40–47 (2004)Kato, S., Yamasaki, N.: Global EDF-based Scheduling with Efficient Priority Promotion. In: Proceedings of the 14th International Conference on Embedded and Real-Time Computing Systems and Applications, August 25-27, pp. 197–206. IEEE Computer Society, Kaohisung (2008)Malardalen Real-Time Research Center, Vasteras, Sweden: WCET Analysis Project. WCET Benchmark Programs (2006), [Online], http://www.mrtc.mdh.se/projects/wcet/March, J., Sahuquillo, J., Hassan, H., Petit, S., Duato, J.: A New Energy-Aware Dynamic Task Set Partitioning Algorithm for Soft and Hard Embedded Real-Time Systems. To be published on The Computer Journal (2011)McNairy, C., Bhatia, R.: Montecito: A Dual-Core, Dual-Thread Itanium Processor. IEEE Micro 25(2), 10–20 (2005)Seo, E., Jeong, J., Park, S., Lee, J.: Energy Efficient Scheduling of Real-Time Tasks on Multicore Processors. IEEE Transactions on Parallel and Distributed Systems 19(11), 1540–1552 (2008)Shah, A.: Arm plans to add multithreading to chip design. ITworld (2010), [Online], http://www.itworld.com/hardware/122383/arm-plans-add-multithreading-chip-designUbal, R., Sahuquillo, J., Petit, S., López, P.: Multi2Sim: A Simulation Framework to Evaluate Multicore-Multithreaded Processors. In: Proceedings of the 19th International Symposium on Computer Architecture and High Performance Computing, October 24-27, pp. 62–68. IEEE Computer Society, Gramado (2007)Watanabe, R., Kondo, M., Imai, M., Nakamura, H., Nanya, T.: Task Scheduling under Performance Constraints for Reducing the Energy Consumption of the GALS Multi-Processor SoC. In: Proceedings of the Design Automation and Test in Europe, April 16-20, pp. 797–802. ACM, Nice (2007)Wei, Y., Yang, C., Kuo, T., Hung, S.: Energy-Efficient Real-Time Scheduling of Multimedia Tasks on Multi-Core Processors. In: Proceedings of the 25th Symposium on Applied Computing, March 22-26, pp. 258–262. ACM, Sierre (2010)Wu, Q., Martonosi, M., Clark, D.W., Reddi, V.J., Connors, D., Wu, Y., Lee, J., Brooks, D.: A Dynamic Compilation Framework for Controlling Microprocessor Energy and Performance. In: Proceedings of the 38th Annual IEEE/ACM International Symposium on Microarchitecture, November 12-16, pp. 271–282. IEEE Computer Society, Barcelona (2005)Zheng, L.: A Task Migration Constrained Energy-Efficient Scheduling Algorithm for Multiprocessor Real-time Systems. In: Proceedings of the International Conference on Wireless Communications, Networking and Mobile Computing, September 21-25, pp. 3055–3058. IEEE Computer Society, Shanghai (2007

    Proteomic Modeling for HIV-1 Infected Microglia-Astrocyte Crosstalk

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    Background: HIV-1-infected and immune competent brain mononuclear phagocytes (MP; macrophages and microglia) secrete cellular and viral toxins that affect neuronal damage during advanced disease. In contrast, astrocytes can affect disease by modulating the nervous system’s microenvironment. Interestingly, little is known how astrocytes communicate with MP to influence disease. Methods and Findings: MP-astrocyte crosstalk was investigated by a proteomic platform analysis using vesicular stomatitis virus pseudotyped HIV infected murine microglia. The microglial-astrocyte dialogue was significant and affected microglial cytoskeleton by modulation of cell death and migratory pathways. These were mediated, in part, through F-actin polymerization and filament formation. Astrocyte secretions attenuated HIV-1 infected microglia neurotoxicity and viral growth linked to the regulation of reactive oxygen species. Conclusions: These observations provide unique insights into glial crosstalk during disease by supporting astrocytemediated regulation of microglial function and its influence on the onset and progression of neuroAIDS. The results open new insights into previously undisclosed pathogenic mechanisms and open the potential for biomarker discovery an

    Metabolic Turnover of Synaptic Proteins: Kinetics, Interdependencies and Implications for Synaptic Maintenance

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    Chemical synapses contain multitudes of proteins, which in common with all proteins, have finite lifetimes and therefore need to be continuously replaced. Given the huge numbers of synaptic connections typical neurons form, the demand to maintain the protein contents of these connections might be expected to place considerable metabolic demands on each neuron. Moreover, synaptic proteostasis might differ according to distance from global protein synthesis sites, the availability of distributed protein synthesis facilities, trafficking rates and synaptic protein dynamics. To date, the turnover kinetics of synaptic proteins have not been studied or analyzed systematically, and thus metabolic demands or the aforementioned relationships remain largely unknown. In the current study we used dynamic Stable Isotope Labeling with Amino acids in Cell culture (SILAC), mass spectrometry (MS), Fluorescent Non-Canonical Amino acid Tagging (FUNCAT), quantitative immunohistochemistry and bioinformatics to systematically measure the metabolic half-lives of hundreds of synaptic proteins, examine how these depend on their pre/postsynaptic affiliation or their association with particular molecular complexes, and assess the metabolic load of synaptic proteostasis. We found that nearly all synaptic proteins identified here exhibited half-lifetimes in the range of 2-5 days. Unexpectedly, metabolic turnover rates were not significantly different for presynaptic and postsynaptic proteins, or for proteins for which mRNAs are consistently found in dendrites. Some functionally or structurally related proteins exhibited very similar turnover rates, indicating that their biogenesis and degradation might be coupled, a possibility further supported by bioinformatics-based analyses. The relatively low turnover rates measured here (∼0.7% of synaptic protein content per hour) are in good agreement with imaging-based studies of synaptic protein trafficking, yet indicate that the metabolic load synaptic protein turnover places on individual neurons is very substantial

    Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

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    IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570
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