Achieving parallel performance and scalability involves making compromises between parallel and sequential computation. If not contained, the overheads of parallelism can easily outweigh its benefits, sometimes by orders of magnitude. Today, we expect ...

Existing tensor compilers have proven their effectiveness in deploying deep neural networks on general-purpose hardware like CPU and GPU, but optimizing for neural processing units (NPUs) is still challenging due to the heterogeneous compute units and ...

With the recent launch of the Intel Optane memory platform, non-volatile main memory in the form of fast, dense, byte-addressable non-volatile memory has now become available. Nevertheless, designing crash-resilient algorithms and data structures is ...

Program synthesis tasks are commonly specified via input-output examples. Existing enumerative techniques for such tasks are primarily guided by program syntax and only make indirect use of the examples. We identify a class of synthesis algorithms for ...

Since the introduction of CompCert, researchers have been refining its language semantics and correctness theorem, and used them as components in software verification efforts. Meanwhile, artifacts ranging from CPU designs to network protocols have been ...

Hardware tracing modules such as Intel Processor Trace perform continuous control-flow tracing of an end-to-end program execution with an ultra-low overhead. PT has been used in a variety of contexts to support applications such as testing, debugging, ...

As the demand for machine learning–based inference increases in tandem with concerns about privacy, there is a growing recognition of the need for secure machine learning, in which secret models can be used to classify private data without the model or ...

Recent transformation-based approaches to compiler testing look for mismatches between the results of pairs of equivalent programs, where one program is derived from the other by randomly applying semantics-preserving transformations. We present a ...

Rust’s type system ensures the safety of Rust programs; however, programmers can side-step some of the strict typing rules by using the unsafe keyword. A common use of unsafe Rust is by libraries. Bugs in these libraries undermine the safety of the ...

Deep Neural Networks (DNNs) have emerged as the core enabler of many major applications on mobile devices. To achieve high accuracy, DNN models have become increasingly deep with hundreds or even thousands of operator layers, leading to high memory and ...

Local data-race-freedom guarantees, ensuring strong semantics for locations accessed by non-racy instructions, provide a fruitful methodology for modular reasoning in relaxed memory concurrency. We observe that standard compiler optimizations are in ...

Intermittently powered energy-harvesting devices enable new applications in inaccessible environments. Program executions must be robust to unpredictable power failures, introducing new challenges in programmability and correctness. One hard problem is ...

We present a system for inductive program synthesis called DreamCoder, which inputs a corpus of synthesis problems each specified by one or a few examples, and automatically derives a library of program components and a neural search policy that can be ...

We present the Sum-Product Probabilistic Language (SPPL), a new probabilistic programming language that automatically delivers exact solutions to a broad range of probabilistic inference queries. SPPL translates probabilistic programs into sum-product ...

Modern field-programmable gate arrays (FPGAs) have recently powered high-profile efficiency gains in systems from datacenters to embedded devices by offering ensembles of heterogeneous, reconfigurable hardware units. Programming stacks for FPGAs, ...

Cache behavior is one of the major factors that influence the performance of applications. Most of the existing compiler techniques that target cache memories focus exclusively on reducing data reuse distances in time (DIT). However, current manycore ...

Strong eventual consistency (SEC) has been used as a classic notion of correctness for Conflict-Free Replicated Data Types (CRDTs). However, it does not give proper abstractions of functionality, thus is not helpful for modular verification of client ...

Implementations of many data structures use several correlated fields to improve their performance; however, inconsistencies between these fields can be a source of serious program errors. To address this problem, we propose a new technique for ...

Text editing is powerful, but some types of expressions are more naturally represented and manipulated graphically. Examples include expressions that compute colors, music, animations, tabular data, plots, diagrams, and other domain-specific data ...

Stan is a probabilistic programming language that is popular in the statistics community, with a high-level syntax for expressing probabilistic models. Stan differs by nature from generative probabilistic programming languages like Church, Anglican, or ...