26,098 papers · page 103 of 1,305
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 optimization opportunities…
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 the program, requiring up…
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 debugging information in …
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 modularity, performance and frame…
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 an empty or full queue wil…
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 explore data reuse opportunitie…
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 import it as a function that…
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 generator that harnesses th…
This paper addresses the need for automatic and efficient generation of host driver code for arbitrary custom AXI-based accelerators targeting linear algebra algorithms, an important workload in various applications, including machine learning and scientific computing. While exis…
Decompilation is a well-studied area with numerous high-quality tools available. These are frequently used for security tasks and to port legacy code. However, they regularly generate difficult-to-read programs and require a large amount of engineering effort to support new progr…
Learning to program involves building a mental representation of how a machine executes instructions and stores data in memory. To help students, teachers often use visual representations to illustrate the execution of programs or particular concepts in their lectures. As a famou…
The optimization of the matrix multiplication (or GEMM) has been a need during the last decades. This operation is considered the flagship of current linear algebra libraries such as BLIS, OpenBLAS, or Intel OneAPI because of its widespread use in a large variety of scientific ap…
Regular Expressions (REs) matching is crucial to identify strings exhibiting certain morphological properties in a data stream, resulting paramount in contexts such as deep packet inspection in computer security and genome analysis in bioinformatics. Yet, due to their intrinsic d…
Polyhedral techniques have been widely used for automatic code optimization in low-level compilers and higher-level processes. Loop optimization is central to this technique, and several polyhedral schedulers like Feautrier, Pluto, isl and Tensor Scheduler have been proposed, eac…
Accelerating programs is typically done by recognizing code idioms matching high-performance libraries or hardware interfaces. However, recognizing such idioms automatically is challenging. The idiom recognition machinery is difficult to write and requires expert knowledge. In ad…
Python has become an increasingly popular programming language, especially in the areas of data analytics and machine learning. Many modern Python packages employ a multi-layer design: the Python layer manages various packages and expresses high-level algorithms; the native layer…
Low compilation times are highly important in contexts of Just-in-time compilation. This not only applies to language runtimes for Java, WebAssembly, or JavaScript, but is also crucial for database systems that employ query compilation as the primary measure for achieving high th…
It is very difficult to thoroughly test a compiler, and as a consequence it is common for released versions of production compilers to contain bugs that cause them to crash and to emit incorrect object code. We created alive-mutate, a mutation-based fuzzing tool that takes test c…
Achieving high performance for Sparse Matrix-Matrix Multiplication (SpMM) has received increasing research attention, especially on multi-core CPUs, due to the large input data size in applications such as graph neural networks (GNNs). Most existing solutions for SpMM computation…
Finding bugs is key to the correctness of compilers in wide use today. If the behaviour of a compiled program, as allowed by its architecture memory model, is not a behaviour of the source program under its source model, then there is a bug. This holds for all programs, but we fo…