![]() Userspace bypass requires no modification to userspace binaries or code, achieving full binary compatibility. In this paper, we propose another approach, userspace bypass, to accelerate syscall-intensive applications, by transparently moving userspace instructions into kernel. Nonetheless, such solutions require developers to refactor their applications, or even update hardware, which impedes their broad adoption. To accelerate such applications, efforts have been made to remove syscalls from the I/O paths, mainly by combining drivers and apps in the same space, or batching syscalls. ![]() The overhead is further amplified by security mechanisms like KPTI. On dealing with the problem of oversubscription (i.e., more threads than cores), RON-plock can solve this problem in constant space complexity and its performance is 3.7 times and 18.9 times better than ShflLock-B and C-BO-MCS-B, respectively.Ĭontext switching between kernel mode and user mode often causes prominent overhead, which slows down applications with frequent system calls (or syscalls), like applications with high I/O. In terms of kernel space performance, compared with using ShflLock, RON in the Linux kernel can improve the performance of Google LevelDB by 1.8 times. In terms of user space performance (by implementing the algorithms in user space library), compared with ShflLock and C-BO-MCS, RON increases the performance of Google LevelDB by 22.1% and 24.2%, respectively. ![]() We use microbenchmarks for quantitative analysis and use multi-core benchmarks to understand the performance under various workloads. Based on the locking-unlocking order, RON delivers locks and data in a one-way circular manner among cores to achieve (1) minimized global data movement cost and (2) bounded waiting time, because there are more threads waiting for the lock on the to-be-visited cores than those on the recently-visited cores and each core will be visited within a bounded waiting time. In RON, we pre-calculate a global optimized locking-unlocking order for a thread to enter the critical section. We propose a method called Routing on Network-on-chip (RON) to minimize communication cost between cores by using a routing table. The difficulty of this problem is that the reduction in communication cost cannot compensate for the increase in the time complexity of the spinlocks. Thus, the large amount of low- and variable-cost data sharing between cores limits the scalability of a multi-core processor. However, a non-uniform memory access (NUMA)-aware algorithm only considers the transmission delay between processors, so it may not be able to fully utilize the connection network of a multi-core processor. Additionally, the more processor cores there are, the longer the farthest transmission distance is. The evaluation shows that TCLocks provide up to 5.2x performance improvement compared with recent locking algorithms.Īs the number of cores increases, the efficiency of accessing shared variables through the lock-unlock method decreases. Using transparent delegation, we design a family of locking protocols (TCLocks), which require zero modification to applications' logic. The lock holder executes the shipped critical section on the waiter's behalf using a light-weight context switch. We propose transparent delegation, in which a waiter automatically encodes its critical section information on its stack and notifies the waiter. However, such locks require modifying applications to explicitly package the critical section, which makes it virtually infeasible for complicated applications with large code-bases, such as the Linux kernel. Meanwhile, some locks avoid this shared data movement by localizing the access to shared data on one core, and shipping the critical section to that specific core. This design adds unavoidable critical path latency leading to performance scalability issues. Locks, as used in practice, move the lock-guarded shared data to the core holding it, which leads to shared data transfer among cores. While locks ensure mutual exclusion of shared data, their design impacts application scalability. Today's high-performance applications heavily rely on various synchronization mechanisms, such as locks.
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