Lock-free Concurrent Data Structures

Concurrent data structures are the data sharing side of parallel programming. Data structures give the means to the program to store data, but also provide operations to the program to access and manipulate these data. These operations are implemented through algorithms that have to be efficient. In the sequential setting, data structures are crucially important for the performance of the respective computation. In the parallel programming setting, their importance becomes more crucial because of the increased use of data and resource sharing for utilizing parallelism. The first and main goal of this chapter is to provide a sufficient background and intuition to help the interested reader to navigate in the complex research area of lock-free data structures. The second goal is to offer the programmer familiarity to the subject that will allow her to use truly concurrent methods.Comment: To appear in "Programming Multi-core and Many-core Computing Systems", eds. S. Pllana and F. Xhafa, Wiley Series on Parallel and Distributed Computin

Split, Send, Reassemble: A Formal Specification of a CAN Bus Protocol Stack

We present a formal model for a fragmentation and a reassembly protocol running on top of the standardised CAN bus, which is widely used in automotive and aerospace applications. Although the CAN bus comes with an in-built mechanism for prioritisation, we argue that this is not sufficient and provide another protocol to overcome this shortcoming.Comment: In Proceedings MARS 2017, arXiv:1703.0581

SUMC/MPOS/HAL interface study

The implementation of the HAL/S language on the IBM-360, and in particular the mechanization of its real time, I/O, and error control statements within the OS-360 environment is described. The objectives are twofold: (1) An analysis and general description of HAL/S real time, I/O, and error control statements and the structure required to mechanize these statements. The emphasis is on describing the logical functions performed upon execution of each HAL statement rather than defining whether it is accomplished by the compiler or operating system. (2) An identification of the OS-360 facilities required during execution of HAL/S code as implemented for the current HAL/S-360 compiler; and an evaluation of the aspects involved with interfacing HAL/S with the SUMC operating system utilizing either the HAL/S-360 compiler or by designing a new HAL/S-SUMC compiler

Non-blocking Priority Queue based on Skiplists with Relaxed Semantics

Priority queues are data structures that store information in an orderly fashion. They are of tremendous importance because they are an integral part of many applications, like Dijkstra’s shortest path algorithm, MST algorithms, priority schedulers, and so on. Since priority queues by nature have high contention on the delete_min operation, the design of an efficient priority queue should involve an intelligent choice of the data structure as well as relaxation bounds on the data structure. Lock-free data structures provide higher scalability as well as progress guarantee than a lock-based data structure. That is another factor to be considered in the priority queue design. We present a relaxed non-blocking priority queue based on skiplists. We address all the design issues mentioned above in our priority queue. Use of skiplists allows multiple threads to concurrently access different parts of the skiplist quickly, whereas relaxing the priority queue delete_min operation distributes contention over the skiplist instead of just at the front. Furthermore, a non-blocking implementation guarantees that the system will make progress even when some process fails. Our priority queue is internally composed of several priority queues, one for each thread and one shared priority queue common to all threads. Each thread selects the best value from its local priority queue and the shared priority queue and returns the value. In case a thread is unable to delete an item, it tries to spy items from other threads\u27 local priority queues. We experimentally and theoretically show the correctness of our data structure. We also compare the performance of our data structure with other variations like priority queues based on coarse-grained skiplists for both relaxed and non-relaxed semantics