Tasks Fairness Scheduler for GPU

Nowadays GPU clusters are available in almost every data processing center. Their GPUs are typically shared by different applications that might have different processing needs and/or different levels of priority. As current GPUs do not support hardware-based preemption mechanisms, it is not possible to ensure the required Quality of Service (QoS) when application kernels are offloaded to devices. In this work, we present an efficient software preemption mechanism with low overhead that evicts and relaunches GPU kernels to provide support to different preemptive scheduling policies. We also propose a new fairness-based scheduler named Fair and Responsive Scheduler, (FRS), that takes into account the current value of the kernels slowdown to both select the new kernel to be launched and establish the time interval it is going to run (quantum).Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

An Efficient and Transparent Thread Migration Scheme in the PM2 Runtime System

International audienceThis paper describes a new iso-address approach to the dynamic allocation of data in a multithreaded runtime system with thread migration capability. The system guarantees that the migrated threads and their associated static data are relocated exactly at the same virtual address on the destination nodes, so that no post-migration processing is needed to keep pointers valid. In the experiments reported, a thread can be migrated in less than 75μs

Prediction-based virtual instance migration for balanced workload in the cloud datacenters

Datacenters in the cloud today provide virtualized resources of CPU, memory, disk, and networks so that millions of users can use the services at the same time in an efficient and scalable way. One of the major challenges in these datacenters is load balancing and shifting. As a huge number of requests are sent to a particular datacenter or a group of servers are asked to process more than their fair share, some of the servers are overloaded, slowed down, hot spots are created, and even hardware failures may occur. This unbalanced load in the end deteriorates the performance of the entire system easily. In this paper, we propose a load balancer that aims at alleviating hot spots and distributing the load from overloaded servers to underutilized servers. Our load balancer monitors the loads of the servers, detects indications of overloading, then migrates virtual instances from overloaded servers to target servers. We have implemented the load balancer in a real system using the Xen hypervisor. We have also conducted an event-driven simulation to evaluate the performance of our system on a large-scale. Our results indicate that our reactive-predictive load balancing algorithm helps balance load among servers in the cloud as much as the best-case scenario from the exhaustive search with much less overhead

Single system image: A survey

Single system image is a computing paradigm where a number of distributed computing resources are aggregated and presented via an interface that maintains the illusion of interaction with a single system. This approach encompasses decades of research using a broad variety of techniques at varying levels of abstraction, from custom hardware and distributed hypervisors to specialized operating system kernels and user-level tools. Existing classification schemes for SSI technologies are reviewed, and an updated classification scheme is proposed. A survey of implementation techniques is provided along with relevant examples. Notable deployments are examined and insights gained from hands-on experience are summarized. Issues affecting the adoption of kernel-level SSI are identified and discussed in the context of technology adoption literature