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Fast compilation is essential for JIT-compilation use cases like dynamic languages or databases as well as development productivity when compiling static languages. Template-based compilation allows fast compilation times, but in existing approaches, ...

Heterogeneous hardware platforms that leverage application-specific hardware accelerators are becoming increasingly popular as the demand for high-performance compute intensive applications rises. The design of such high-performance hardware accelerators ...

Optimizing compilers employ a rich set of transformations that generate highly efficient code for a variety of source languages and target architectures. These transformations typically operate on general control flow constructs which trigger a range of ...

Parser generators have long been a savior for programmers, liberating them from the daunting task of crafting correct and maintainable parsers. Yet, this much-needed simplicity often comes at the expense of efficiency.

We present, Paguroidea, a parser ...

Data-structure splicing techniques, such as structure splitting, field reordering, and pointer inlining reorganize data structures to improve cache and translation look-aside buffer (TLB) utilization. Structure types are typically transformed globally in ...

Existing program analysis tools for Rust lack the ability to effectively detect security vulnerabilities due to the absence of an accurate call graph and precise points-to information. We present Rupta, the first context-sensitive pointer analysis ...

Embedded systems are ubiquitous, but in order to maximize their lifetime on batteries there is a need for faster code execution – i.e., higher energy efficiency, and for reduced memory usage. The large number of sensors integrated into embedded systems ...

Heterogeneous-ISA processor designs have attracted considerable research interest. However, unlike their homogeneous-ISA counterparts, explicit software support for bridging ISA heterogeneity is required. The lack of a compilation toolchain ready to ...

Message queues are used widely in parallel processing systems for worker thread synchronization. When there is a throughput mismatch between the upstream and downstream tasks, the message queue buffer will often exist as either empty or full. Polling on ...

GPUs are increasingly being used used to speed up Python applications in the scientific computing and machine learning domains. Currently, the two common approaches to leveraging GPU acceleration in Python are 1) create a custom native GPU kernel, and ...

Many debugging tools rely on compiler-produced metadata to present a source-language view of program states, such as variable values and source line numbers. While this tends to work for unoptimised programs, current compilers often generate only partial ...

Amdahl's law implies that even small sequential bottlenecks can seriously limit the scalability of multi-threaded programs. To achieve scalability, developers must painstakingly identify sequential bottlenecks in their program and eliminate these ...

An exact profiler inserts counters in a program to record how many times each edge of that program's control-flow graph has been traversed during an execution of it. It is common practice to instrument only edges in the complement of a minimum spanning ...

Profile-guided optimizations rely on profile data for directing compilers to generate optimized code. To achieve the maximum performance boost, profile data needs to be collected on the same version of the binary that is being optimized. In practice ...

Fault attacks present unique safety and security challenges that require dedicated countermeasures, even for bug-free programs. Models of these complex attacks are made workable by approximating their effects to a suitable level of abstraction. The ...

We present Clog, a declarative language for describing static code checkers for C. Unlike other extensible state-of-the-art checker frameworks, Clog enables powerful interprocedural checkers without exposing the underlying program representation: Clog ...

Running machine learning (ML) on low-power IoT devices exposes unique security concerns. Attackers can easily steal or manipulate sensitive user data or proprietary ML models from the devices’ off-chip memory by leveraging their simple hardware structure ...

We address the challenges associated with deploying neural networks on CPUs, with a particular focus on minimizing inference time while maintaining accuracy. Our novel approach is to use the dataflow (i.e., computation order) of a neural network to ...

This paper introduces ORXESTRA, a context-aware execution time prediction model based on Transformers XL, specifically designed to accurately estimate performance in embedded system applications. Unlike traditional machine learning models that often ...

There is a growing interest in enhancing compiler optimizations with ML models, yet interactions between compilers and ML frameworks remain challenging. Some optimizations require tightly coupled models and compiler internals, raising issues with ...

Applying compilation transformations in optimal sequences can significantly improve program speed and reduce code size. However, finding these optimal sequences—a problem known as the phase-ordering problem—remains a long-standing challenge. Specifically,...