Verifiably correct high-performance concurrency libraries for multi-core computing systems

The benefits of fast computer systems are clear - improving performance allows more sophisticated applications to be developed. Speed-up via higher processor clock speeds, however, reached a physical upper limit in the early 2000s, with power-dissipation becoming a major issue. Hardware designers have therefore switched to multicore processors with fixed clock speeds, where speed-up is achieved by including several cores in a single processor. Multicore processors are now pervasive in all aspects of computing, from cluster servers and desktops to low-power mobile devices.

A multicore processor efficiently executes concurrent programs comprising multiple threads by allowing several computations to take place simultaneously in the different cores. These threads communicate via synchronised access and modification of shared resources stored in shared memory. While some problems (coined embarrassingly parallel problems) are naturally able to take advantage of multicore computing, the majority require clever management of thread synchronisation that is difficult to achieve. Moreover, modern architectures have forced programmers to understand intricate details of the hardware/software interface in addition to concurrency issues within the programs they develop.

Within a multicore processor, each processing core has access to a local buffer that acts as a temporary cache - any writes stored in a local buffer are not visible to other cores until the buffer is flushed. For efficiency reasons, multicore architectures implement so-called relaxed-memory models, where read and write events within a single thread may take effect in shared memory out-of-order, leading to behaviours that may not be expected by a programmer. Restoring correctness requires manual introduction of "fence" instructions in a program's code, which is a non-trivial task - under-fencing leads to incorrect behaviours, while overfencing leads to inefficient programs. Therefore, as Shavit states, "The advent of multicore processors as the standard computing platform will force major changes in software design." There is a large international effort in both academia and industry to make better use of multicore processing, ranging from new foundational and theoretical underpinnings to the development of novel abstractions, tool support, engineering paradigms, etc.

In this project, we aim to simplify system development via practical solutions that are highly performant (to increase efficiency), verifiably correct (to ensure dependability) and cope with relaxed-memory models (as used by modern hardware). In particular, we develop efficient "concurrent objects" that provide abstractions from the low-level hardware interface and manage thread synchronisation on behalf of a programmer. Concurrent objects are to ultimately become part of a programming language library - some languages e.g., Java already offer basic concurrent objects as part of their standard library - hence are highly applicable.

The objects we deliver will take advantage of relaxed memory models. Here, it is well known that correctness conditions that are too strict (e.g., linearizability) are themselves becoming a barrier to efficiency.
We therefore begin by developing new theoretical foundations in the form of relaxed correctness conditions that match relaxed memory models. A hierachy of different conditions will be developed, enabling one to easily determine the relative strengths of each condition. These conditions will be linked to a contextual notion of refinement to provide a basis for substitutability in client programs. This provides a basis for more efficient, verifiably correct, concurrent objects for relaxed memory models. We will focus on developing concurrent data structures (e.g., stacks, queues, deques) for the TSO memory model. Their verification will be mechanised in the KIV theorem prover to eliminate human error in verification, which in turn improves dependability.

This work will have impact on three key areas.

Academic. This work covers the areas of concurrency theory, programming languages, algorithm development and verification, and hence, researchers from these areas will be the primary beneficiaries. Academically, we will produce scientific innovations that present new ways of thinking about correctness of a concurrent object, develop new concurrent object designs as proofs of concept, and new verifications of these objects. Correctness notions for concurrent objects are adapted from distributed computing and databases, and hence our insights gained in the multicore context can be fed back into both of these areas. On a wider scale, this project will enable us to deepen our understanding of concurrent systems, by learning from the abstractions and logics we use to verify the concurrent objects we develop.

Industrial. The project covers foundational aspects of concurrent systems, and hence, is industrially relevant to many different types of companies.
- Hardware manufacturers, e.g., IBM, Intel, AMD, and ARM, who require better-performing software to justify introduction of additional cores in the processors they produce. Without software-side improvements, end-users will see minimal improvements from processors with more cores.
- Programming language developers, e.g., Java (Oracle), C++, Scala, Python, who use predefined libraries to provide high-end functionality to programmers in a layered re-usable manner.
- Application developers, e.g., Valve Software (video gaming), Codeplay Software (SoC tools), etc., who require reliable high-performance libraries to take advantage of the available multi-core hardware.
- Formal verification companies, e.g., http://formalmethods.wikia.com/wiki/Companies, who will benefit from the techniques we use to verify novel concurrent data structures for relaxed memory. Of particular interest will be the mechanisations we develop in KIV.
- Large-scale developers, e.g., Google, Facebook and Amazon, who are interested in correctness conditions such as causal and eventual consistency in the databases they use. There is a direct link between the correctness conditions studied in WP1 and such notions of consistency.

Societal. There is no doubt that faster computing is the cornerstone of improving modern life, with an endless list of examples forming a wide range of real-world scenarios - improving personal interactions with end-user devices, connecting ever more devices to both centralised and distributed servers, processing vast quantities of data for commercial and scientific use, enhancing security for commerce, etc. There is an increasing dependence on computerised systems that control an ever-larger proportion of security-, mission- and safety-critical systems, e.g., railways, power distribution systems, spacecraft, etc, all of which are inherently concurrent and, in addition, reliability is of utmost importance.