736 papers · page 6 of 37
The increasing vulnerability of microprocessors due to frequent silicon faults greatly exacerbates the risks of silent data corruption. Existing software-based schemes to detect these suffer from high power and performance overhead. State-of-the-art hardware fault-tolerance techn…
Fully homomorphic encryption (FHE) and zero-knowledge proofs (ZKPs) are emerging as solutions for data security in distributed environments. However, the widespread adoption of these encryption techniques is hindered by their significant computational overhead, primarily resultin…
Fully Homomorphic Encryption (FHE), particularly the CKKS scheme, enables computation on encrypted data, facilitating secure task offloading to untrusted servers. CKKS allows packing multiple complex values into a single ciphertext, crucial for fixed-point arithmetic in machine l…
We introduce VEGA, an AI-driven system aimed at easing the development of compiler backends for new targets. Our approach involves categorizing functions from existing backends into function groups, each comprising various target-specific implementations of a standard compiler in…
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…
Modern processors with large multi-banked register files often rely on hardware solutions to resolve bank conflicts efficiently. However, these hardware-based methods, while flexible, can incur runtime penalties and restrict the exploration of optimized hardware designs. In contr…
Despite decades of improvement in compiler technology, it remains necessary to profile applications to improve performance. Existing profiling tools typically either sample hardware performance counters or instrument the program with extra instructions to analyze its execution. B…
Computing gradients is a crucial task in many domains, including machine learning, physics simulations, and scientific computing. Automatic differentiation (AD) computes gradients for arbitrary imperative code. In reverse mode AD, an auxiliary structure, the tape, is used to tran…
Incremental builds are commonly employed in software development, involving minor changes to existing source code that is then frequently recompiled. Speeding up incremental builds not only enhances the software development workflow but also improves CI/CD systems by enabling fas…