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Memory profiling captures programs’ dynamic memory behavior, assisting programmers in debugging, tuning, and enabling advanced compiler optimizations like speculation-based automatic parallelization. As each use case demands its unique program trace summary, various memory profiler types have been developed. Yet, designing practical memory profilers often requires extensive compiler expertise, adeptness in program optimization, and significant implementation effort. This often results in a void where aspirations for fast and robust profilers remain unfulfilled. To bridge this gap, this paper presents PROMPT, a framework for streamlined development of fast memory profilers. With PROMPT, developers need only specify profiling events and define the core profiling logic, bypassing the complexities of custom instrumentation and intricate memory profiling components and optimizations. Two state-of-the-art memory profilers were ported with PROMPT where all features preserved. By focusing on the core profiling logic, the code was reduced by more than 65% and the profiling overhead was improved by 5.3× and 7.1× respectively. To further underscore PROMPT’s impact, a tailored memory profiling workflow was constructed for a sophisticated compiler optimization client. In 570 lines of code, this redesigned workflow satisfies the client’s memory profiling needs while achieving more than 90% reduction in profiling overhead and improved robustness compared to the original profilers. 

Modern and emerging architectures demand increasingly complex compiler analyses and transformations. As the emphasis on compiler infrastructure moves beyond support for peephole optimizations and the extraction of instruction-level parallelism, compilers should support custom tools designed to meet these demands with higher-level analysis-powered abstractions and functionalities of wider program scope. This paper introduces NOELLE, a robust open-source domain-independent compilation layer built upon LLVM providing this support. NOELLE extends abstractions and functionalities provided by LLVM enabling advanced, program-wide code analyses and transformations. This paper shows the power of NOELLE by presenting a diverse set of 11 custom tools built upon it. 

Type-safe languages improve application safety by eliminating whole classes of vulnerabilities–such as buffer overflows–by construction. However, this safety sometimes comes with a performance cost. As a result, many modern type-safe languages provide escape hatches that allow developers to manually bypass them. The relative value of performance to safety and the degree of performance obtained depends upon the application context, including user goals and the hardware upon which the application is to be executed. Since libraries may be used in many different contexts, library developers cannot make safety-performance trade-off decisions appropriate for all cases. Application developers can tune libraries themselves to increase safety or performance, but this requires extra effort and makes libraries less reusable. To address this problem, we present NADER, a Rust development tool that makes applications safer by automatically transforming unsafe code into equivalent safe code according to developer preferences and application context. In end-to-end system evaluations in a given context, NADER automatically reintroduces numerous library bounds checks, in many cases making application code that uses popular Rust libraries safer with no corresponding loss in performance. 

Software security techniques rely on correct execution by the hardware. Securing hardware components has been challenging due to their complexity and the proportionate attack surface they present during their design, manufacture, deployment, and operation. Recognizing that external communication represents one of the greatest threats to a system's security, this paper introduces the TrustGuard containment architecture. TrustGuard contains malicious and erroneous behavior using a relatively simple and pluggable gatekeeping hardware component called the Sentry. The Sentry bridges a physical gap between the untrusted system and its external interfaces. TrustGuard allows only communication that results from the correct execution of trusted software, thereby preventing the ill effects of actions by malicious hardware or software from leaving the system. The simplicity and pluggability of the Sentry, which is implemented in less than half the lines of code of a simple in-order processor, enables additional measures to secure this root of trust, including formal verification, supervised manufacture, and supply chain diversification with less than a 15% impact on performance.