Strong Memory Consistency For Parallel Programming

Correctly synchronizing multithreaded programs is challenging, and errors can lead to program failures (e.g., atomicity violations). Existing memory consistency models rule out some possible failures, but are limited by depending on subtle programmer-defined locking code and by providing unintuitive semantics for incorrectly synchronized code. Stronger memory consistency models assist programmers by providing them with easier-to-understand semantics with regard to memory access interleavings in parallel code. This dissertation proposes a new strong memory consistency model based on ordering-free regions (OFRs), which are spans of dynamic instructions between consecutive ordering constructs (e.g. barriers). Atomicity over ordering-free regions provides stronger atomicity than existing strong memory consistency models with competitive performance. Ordering-free regions also simplify programmer reasoning by limiting the potential for atomicity violations to fewer points in the program’s execution. This dissertation explores both software-only and hardware-supported systems that provide OFR serializability

Using Visual Programming Games to Study Novice Programmers

Enabling programmers to write correct and efficient parallel code remains an important challenge, and the prevalence of on-chip accelerators exacerbates this challenge. Novice programmers, especially those in disciplines outside of Computer Science and Computer Engineering, need to be able to write code that exploits parallelism and heterogeneity, but the frameworks for writing parallel and heterogeneous programs expect expert knowledge and experience. More effort must be put into understanding how novice programmers solve parallel problems. Unfortunately, novice programmers are difficult to study because they are, by definition, novices. We have designed a visual programming language and game-based framework for studying how novice programmers solve parallel problems. This tool was used to conduct an initial study on 95 undergraduate students with little to no prior programming experience. 71% of all volunteer participants completed the study in 48 minutes on average. This study demonstrated that novice programmers could solve parallel problems, and this framework can be used to conduct more thorough studies of how novice programmers approach parallel code

ORCA: Ordering-free Regions for Consistency and Atomicity

Writing correct synchronization is one of the main difficulties of multithreaded programming. Incorrect synchronization causes many subtle concurrency errors such as data races and atomicity violations. Previous work has proposed stronger memory consistency models to rule out certain classes of concurrency bugs. However, these approaches are limited by a program’s original (and possibly incorrect) synchronization. In this work, we provide stronger guarantees than previous memory consistency models by punctuating atomicity only at ordering constructs like barriers, but not at lock operations. We describe the Ordering-free Regions for Consistency and Atomicity (ORCA) system which enforces atomicity at the granularity of ordering-free regions (OFRs). While many atomicity violations occur at finer granularity, in an empirical study of many large multithreaded workloads we find no examples of code that requires atomicity coarser than OFRs. Thus, we believe OFRs are a conservative approximation of the atomicity requirements of many programs. ORCA assists programmers by throwing an exception when OFR atomicity is threatened, and, in exception-free executions, guaranteeing that all OFRs execute atomically. In our evaluation, we show that ORCA automatically prevents real concurrency bugs. A user-study of ORCA demonstrates that synchronizing a program with ORCA is easier than using a data race detector. We evaluate modest hardware support that allows ORCA to run with just 18% slowdown on average over pthreads, with very similar scalability

Core Ironclad

Core Ironclad is a core calculus that models the salient features of Ironclad C++, a library-augmented type-safe subset of C++. We give an overview of the language including its definition and key design points. We then prove type safety for the language and use that result to show that the pointer lifetime invariant, a key property of Ironclad C++, holds within the system

Strong Memory Consistency for Parallel Programming

Correctly synchronizing multithreaded programs is challenging, and errors can lead to program failures (e.g., atomicity violations). Existing memory consistency models rule out some possible failures, but are limited by depending on subtle programmer-defined locking code and by providing unintuitive semantics for incorrectly synchronized code. Stronger memory consistency models assist programmers by providing them with easier-to-understand semantics with regard to memory access interleavings in parallel code. This dissertation proposes a new strong memory consistency model based on ordering-free regions (OFRs), which are spans of dynamic instructions between consecutive ordering constructs (e.g. barriers). Atomicity over ordering-free regions provides stronger atomicity than existing strong memory consistency models with competitive performance. Ordering-free regions also simplify programmer reasoning by limiting the potential for atomicity violations to fewer points in the program’s execution. This dissertation explores both software-only and hardware-supported systems that provide OFR serializability

Ironclad C++ A Library-Augmented Type-Safe Subset of C++

C++ remains a widely used programming language, despite retaining many unsafe features from C. These unsafe features often lead to violations of type and memory safety, which manifest as buffer overflows, use-after-free vulnerabilities, or abstraction violations. Malicious attackers are able to exploit such violations to compromise application and system security. This paper introduces Ironclad C++, an approach to bring the benefits of type and memory safety to C++. Ironclad C++ is, in essence, a library-augmented type-safe subset of C++. All Ironclad C++ programs are valid C++ programs, and thus Ironclad C++ programs can be compiled using standard, off-the-shelf C++ compilers. However, not all valid C++ programs are valid Ironclad C++ programs. To determine whether or not a C++ program is a valid Ironclad C++ program, Ironclad C++ uses a syntactic source code validator that statically prevents the use of unsafe C++ features. For properties that are difficult to check statically Ironclad C++ applies dynamic checking to enforce memory safety using templated smart pointer classes. Drawing from years of research on enforcing memory safety, Ironclad C++ utilizes and improves upon prior techniques to significantly reduce the overhead of enforcing memory safety in C++. To demonstrate the effectiveness of this approach, we translate (with the assistance of a semi-automatic refactoring tool) and test a set of performance benchmarks, multiple bug-detection suites, and the open-source database leveldb. These benchmarks incur a performance overhead of 12 % on average as compared to the unsafe original C++ code, which is small compared to prior approaches for providing comprehensive memory safety in C and C++. 1