Memory Access Characterization of OpenMP Workloads on a Multi-core NUMA Machine

Nowadays, on hierarchical shared memory multiprocessors with Non-Uniform Memory Access (NUMA), the number of cores accessing memory banks is considerably high. Such accesses produce more stress on the memory banks, generating load-balancing issues, memory contention and remote accesses. In this context, it is important to have a good understanding of memory access patterns and what are the inuences of data placement on such patterns. In this document, we have investigated memory accesses behavior of microbenchmarks and benchmarks over a ccNUMA platform with multi-core processors. Additionally, we have evaluated a set of memory policies that were used to place data among the machine memory banks. Our results have shown that an appropriate selection of data placement, considering the memory accesses, can generated great improvement gains

Eureka: a distributed shared memory system based on the Lazy Data Merging consistency model

Distributed Shared Memory (DSM) provides an abstraction of shared memory on a network of workstations. Problems with existing DSM systems are lack of portability due to compiler and/or operating system modification requirements, and reduced performance due to significant synchronization and communication costs when compared to their message passing counterparts (e.g., PVM and MPI). Our approach was to introduce a new DSM consistency model, Lazy Data Merging (LDM), which extends Data Merging (DM). LDM is optimized for software runtime implementations and differs from DM by 'lazily' placing data updates across the communication network only when they are required. It is our belief that LDM can significantly reduce communication costs, particularly for applications that make extensive use of locks. We have completed the design of "Eureka", a prototype DSM system that provides a software implementation of the LDM consistency model. To ensure portability and efficiency we use only standard UniXTM system calls and a publicly available software thread package, Cthreads, from the University of Utah. Furthermore, we have implemented and tested some of Eureka's core components, specifically, the set of communication and hybrid (Invalidate/Update) coherence primitives, which are essential for follow on work in building the complete DSM system. The question of efficiency is still an open problem, because we did not compare Eureka with other DSM implementations.http://archive.org/details/eurekadistribute1094535209NANABrazilian Navy author

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

"Virtual malleability" applied to MPI jobs to improve their execution in a multiprogrammed environment"

This work focuses on scheduling of MPI jobs when executing in shared-memory multiprocessors (SMPs). The objective was to obtain the best performance in response time in multiprogrammed multiprocessors systems using batch systems, assuming all the jobs have the same priority. To achieve that purpose, the benefits of supporting malleability on MPI jobs to reduce fragmentation and consequently improve the performance of the system were studied. The contributions made in this work can be summarized as follows:· Virtual malleability: A mechanism where a job is assigned a dynamic processor partition, where the number of processes is greater than the number of processors. The partition size is modified at runtime, according to external requirements such as the load of the system, by varying the multiprogramming level, making the job contend for resources with itself. In addition to this, a mechanism which decides at runtime if applying local or global process queues to an application depending on the load balancing between processes of it. · A job scheduling policy, that takes decisions such as how many processes to start with and the maximum multiprogramming degree based on the type and number of applications running and queued. Moreover, as soon as a job finishes execution and where there are queued jobs, this algorithm analyzes whether it is better to start execution of another job immediately or just wait until there are more resources available. · A new alternative to backfilling strategies for the problema of window execution time expiring. Virtual malleability is applied to the backfilled job, reducing its partition size but without aborting or suspending it as in traditional backfilling. The evaluation of this thesis has been done using a practical approach. All the proposals were implemented, modifying the three scheduling levels: queuing system, processor scheduler and runtime library. The impact of the contributions were studied under several types of workloads, varying machine utilization, communication and, balance degree of the applications, multiprogramming level, and job size. Results showed that it is possible to offer malleability over MPI jobs. An application obtained better performance when contending for the resources with itself than with other applications, especially in workloads with high machine utilization. Load imbalance was taken into account obtaining better performance if applying the right queue type to each application independently.The job scheduling policy proposed exploited virtual malleability by choosing at the beginning of execution some parameters like the number of processes and maximum multiprogramming level. It performed well under bursty workloads with low to medium machine utilizations. However as the load increases, virtual malleability was not enough. That is because, when the machine is heavily loaded, the jobs, once shrunk are not able to expand, so they must be executed all the time with a partition smaller than the job size, thus degrading performance. Thus, at this point the job scheduling policy concentrated just in moldability.Fragmentation was alleviated also by applying backfilling techniques to the job scheduling algorithm. Virtual malleability showed to be an interesting improvement in the window expiring problem. Backfilled jobs even on a smaller partition, can continue execution reducing memory swapping generated by aborts/suspensions In this way the queueing system is prevented from reinserting the backfilled job in the queue and re-executing it in the future