Osman Sarood

• PhD
• University of Illinois Urbana-Champaign

In a design based on the Charm++ parallel programming framework, an adaptive runtime system dynamically interacts with a datacenter's resource manager to control power by intelligently scheduling jobs, reallocating resources, and reconfiguring hardware. It simultaneously manages reliability by cooling the system to the running application's optimal...

Malleable jobs are those which can dynamically shrink or expand the number of processors on which they are executing at runtime in response to an external command. Malleable jobs can significantly improve system utilization and reduce average response time, compared to traditional jobs. To realize these benefits, three components are critical – an...

Building future generation supercomputers while constraining their power consumption is one of the biggest challenges faced by the HPC community. For example, US Department of Energy has set a goal of 20 MW for an exascale (1018 flops) supercomputer. To realize this goal, a lot of research is being done to revolutionize hardware design to build pow...

Extreme-scale computing is set to provide the infrastructure for the advances and breakthroughs that will solve some of the hardest problems in science and engineering. However, resilience and energy concerns loom as two of the major challenges for machines at that scale. The numb.er of components that will be assembled in the supercomputers plays...

Soaring energy consumption, accompanied by declining reliability, together loom as the biggest hurdles for the next generation of supercomputers. Recent reports have expressed concern that reliability at exascale level could degrade to the point where failures become a norm rather than an exception. HPC researchers are focusing on improving existin...

As we move towards the exascale era, power and energy have become major challenges. Some of the supercomputers draw more than 10 megawatts, leading to high energy bills. A significant portion of this energy is spent in cooling. In this paper, we propose an adaptive control system that minimizes the cooling energy by using Dynamic Voltage and Freque...

Energy consumption and power draw pose two major challenges to the HPC community for designing larger systems. Present day HPC systems consume as much as 10MW of electricity and this is fast becoming a bottleneck. Although energy bills will significantly increase with machine size, power consumption is a hard constraint that must be addressed. Inte...

Driven by the benefits of elasticity and pay-as-you-go model, cloud computing is emerging as an attractive alternative and addition to in-house clusters and supercomputers for some High Performance Computing (HPC) applications. However, poor interconnect performance, heterogeneous and dynamic environment, and interference by other virtual machines...

As we move to exascale machines, both peak power demand and total energy consumption have become prominent challenges. A significant portion of that power and energy consumption is devoted to cooling, which we strive to minimize in this work. We propose a scheme based on a combination of limiting processor temperatures using dynamic voltage and fre...

Information Set Generation (ISG) is the identification of the set of paths in an imperfect information game tree that are consistent with a player’s observations. The ability to reason about the possible game history is critical to the performance of game-playing agents. ISG represents a class of combinatorial search problems which is computational...

An exascale machine is expected to be delivered in the time frame 2018-2020. Such a machine will be able to tackle some of the hardest computational problems and to extend our understanding of Nature and the universe. However, to make that a reality, the HPC community has to solve a few important challenges. Resilience will become a prominent probl...

Cloud computing is increasingly being explored as a cost effective alternative and addition to supercomputers for some High Performance Computing (HPC) applications. However, dynamic environment and interference by other virtual machines are some of the factors which prevent efficient execution of HPC applications in cloud. Through this research, w...

As we move to exascale machines, both peak power and total energy consumption have become prominent major challenges. There has been a lot of research on saving machine energy consumption for HPC data centers. However, a significant part of energy consumption for HPC data centers can be attributed to cooling the machine room. We have already shown...

Meeting power requirements of huge exascale machines of the future will be a major challenge. Our focus in this paper is to minimize cooling power and we propose a technique that uses a combination of DVFS and temperature aware load balancing to constrain core temperatures as well as save cooling energy. Our scheme is specifically designed to suit...

Increasing number of cores and clock speeds on a smaller chip area implies more heat dissipation and an ever increasing heat density. This increased heat, in turn, leads to higher cooling cost and occurrence of hot spots. Effective use of dynamic voltage and frequency scaling (DVFS) can help us alleviate this problem. But there is an associated exe...

Meeting power requirements of huge exascale machines of the future will be a major challenge. Our focus in this paper is to minimize cooling power and we propose a technique that uses a combination of DVFS and temperature aware load balancing to constrain core temperatures as well as save cooling energy. Our scheme is specifically designed to suit...