Schedulers used by modern OSs (e.g., Oracle Solaris 11™ and GNU/Linux) balance load by balancing the number of threads in run queues of different cores. While this approach is effective for a single CPU multicore system, we show that it can lead to a significant load imbalance across CPUs of a multi-CPU multicore system. Because different threads of a multithreaded application often exhibit different levels of CPU utilization, load cannot be measured in terms of the number of threads alone. We propose Tumbler that migrates the threads of a multithreaded program across multiple CPUs to balance the load across the CPUs. While Tumbler distributes the threads equally across the CPUs, its assignment of threads to CPUs is aimed at minimizing the variation in utilization of different CPUs to achieve load balance. We evaluated Tumbler using a wide variety of 35 multithreaded applications, and our experimental results show that Tumbler outperforms both Oracle Solaris 11™ and GNU/Linux.

On a cache-coherent multicore multiprocessor system, the performance of a multithreaded application with high lock contention is very sensitive to the distribution of application threads across multiple processors (or Sockets). This is because the distribution of threads impacts the frequency of lock transfers between Sockets, which in turn impacts the frequency of last-level cache (LLC) misses that lie on the critical path of execution. Since the latency of a LLC miss is high, an increase of LLC misses on the critical path increases both lock acquisition latency and critical section processing time. However, thread schedulers for operating systems, such as Solaris and Linux, are oblivious of the lock contention among multiple threads belonging to an application and therefore fail to deliver high performance for multithreaded applications.

On a cache-coherent multicore multiprocessor system, the performance of a multithreaded application with high lock contention is very sensitive to the distribution of application threads across multiple processors. This is because the distribution of threads impacts the frequency of lock transfers between processors, which in turn impacts the frequency of last-level cache (LLC) misses that lie on the critical path of execution. Inappropriate distribution of threads across processors increases LLC misses in the critical path and significantly degrades performance of multithreaded programs. To alleviate the above problem, this paper overviews a thread migration technique, which migrates threads of a multithreaded program across multicore processors so that threads seeking locks are more likely to find the locks on the same processor.

Since multicore systems offer greater performance via parallelism, future computing is progressing towards use of multicore machines with large number of cores. However, the performance of emerging multithreaded programs often does not scale to fully utilize the available cores. Therefore, simultaneously running multiple multithreaded applications becomes inevitable to fully exploit the computing potential of such machines. However, maximizing the performance and throughput on multicore machines in the presence of multiple multithreaded programs is a challenge for the OS. We have observed that the state-of-the-art contention management algorithms fail to effectively coschedule multithreaded programs on multicore machines. To address the above challenge, we present ADAPT, a scheduling framework that continuously monitors the resource usage of multithreaded programs and adaptively coschedules them such that they interfere with each other's performance as little as possible. In addition, ADAPT selects appropriate memory allocation and scheduling policies according to the workload characteristics. We have implemented ADAPT on a 64-core Supermicro server running Solaris 11 and evaluated it using 26 multithreaded programs including the TATP database application, SPECjbb2005, and programs from Phoenix, PARSEC, and SPEC OMP suites. The experimental results show that ADAPT substantially improves total turnaround time and system utilization relative to the default Solaris 11 scheduler.

To realize the performance potential of multicore systems, we must effectively manage the interactions between memory reference behavior and the operating system policies for thread scheduling and migration decisions. We observe that these interactions lead to significant variations in the performance of a given application, from one execution to the next, even when the program input remains unchanged and no other applications are being run on the system. Our experiments with multithreaded programs, including the TATP database application, SPECjbb2005, and a subset of PARSEC and SPEC OMP programs, on a 24-core Dell PowerEdge R905 server running OpenSolaris confirms the above observation. In this work we develop Thread Tranquilizer, an automatic technique for simultaneously reducing performance variation and improving performance by dynamically choosing appropriate memory allocation and process scheduling policies. Thread Tranquilizer uses simple utilities available on modern Operating Systems for monitoring cache misses and thread context-switches and then utilizes the collected information to dynamically select appropriate memory allocation and scheduling policies. In our experiments, Thread Tranquilizer yields up to 98% (average 68%) reduction in performance variation and up to 43% (average 15%) improvement in performance over default policies of OpenSolaris. We also demonstrate that Thread Tranquilizer simultaneously reduces performance variation and improves performance of the programs on Linux. Thread Tranquilizer is easy to use as it does not require any changes to the application source code or the OS kernel.

Efficient contention management is the key to achieving scalable performance for multithreaded applications running on multicore systems. However, contention management policies provided by modern operating systems increase context-switches and lead to performance degradation for multithreaded applications under high loads. Moreover, this problem is exacerbated by the interaction between contention management policies and OS scheduling polices. Time Share (TS) is the default scheduling policy in a modern OS such as Open Solaris and with TS policy, priorities of threads change very frequently for balancing load and providing fairness in scheduling. Due to the frequent ping-ponging of priorities, threads of an application are often preempted by the threads of the same application. This increases the frequency of involuntary context-switches as wells as lock-holder thread preemptions and leads to poor performance. This problem becomes very serious under high loads. To alleviate this problem, in this paper, we present a scheduling policy called Faithful Scheduling (FF), which dramatically reduces context-switches as well as lock-holder thread preemptions. We implemented FF on a 24-core Dell Power Edge R905 server running OpenSolaris.2009.06 and evaluated it using 22 programs including the TATP database application, SPECjbb2005, programs from PARSEC, SPEC OMP, and some micro benchmarks. The experimental results show that FF policy achieves high performance for both lightly and heavily loaded systems. Moreover it does not require any changes to the application source code or the OS kernel.