1,971 papers · page 34 of 99
Concurrent and distributed programming is notoriously hard. Modern languages and toolkits ease this difficulty by offering message-passing abstractions, such as actors (e.g., Erlang, Akka, Orleans) or processes (e.g., Go): they allow for simpler reasoning w.r.t. shared-memory con…
Byte-addressable, non-volatile memory (NVM) is emerging as a revolutionary memory technology that provides persistency, near-DRAM performance, and scalable capacity. To facilitate its use, many NVM programming models have been proposed. However, most models require programmers to…
This paper presents McNetKAT, a scalable tool for verifying probabilistic network programs. McNetKAT is based on a new semantics for the guarded and history-free fragment of Probabilistic NetKAT in terms of finite-state, absorbing Markov chains. This view allows the semantics of …
Scheduling transformations reorder a program’s operations to improve locality and/or parallelism. The polyhedral model is a general framework for composing and applying instance-wise scheduling transformations for loop-based programs, but there is no analogous framework for recur…
Minimizing cache misses has been the traditional goal in optimizing cache performance using compiler based techniques. However, continuously increasing dataset sizes combined with large numbers of cache banks and memory banks connected using on-chip networks in emerging manycores…
Automatically transforming programs is hard, yet critical for automated program refactoring, rewriting, and repair. Multi-language syntax transformation is especially hard due to heterogeneous representations in syntax, parse trees, and abstract syntax trees (ASTs). Our insight i…
Distributed systems offer notable benefits over their centralized counterparts. Reaping these benefits, however, requires burdensome developer effort to identify and rewrite bottlenecked components. Light-touch distribution is a new approach that converts a legacy system into a d…
In a typical data-processing program, the representation of data in memory is distinct from its representation in a serialized form on disk. The former has pointers and arbitrary, sparse layout, facilitating easy manipulation by a program, while the latter is packed contiguously,…
We consider the problem of expected cost analysis over nondeterministic probabilistic programs, which aims at automated methods for analyzing the resource-usage of such programs. Previous approaches for this problem could only handle nonnegative bounded costs. However, in many sc…
Modern data-parallel systems such as Spark rely increasingly on in-memory computing that can significantly improve the efficiency of iterative algorithms. To process real-world datasets, modern data-parallel systems often require extremely large amounts of memory, which are both …
Recent work on formal verification of differential privacy shows a trend toward usability and expressiveness -- generating a correctness proof of sophisticated algorithm while minimizing the annotation burden on programmers. Sometimes, combining those two requires substantial cha…
Distributed systems often replicate data at multiple locations to achieve availability despite network partitions. These systems accept updates at any replica and propagate them asynchronously to every other replica. Conflict-Free Replicated Data Types (CRDTs) provide a principle…
Analyzing the behavior of a program running on a processor that supports speculative execution is crucial for applications such as execution time estimation and side channel detection. Unfortunately, existing static analysis techniques based on abstract interpretation do not mode…
This paper proposes TaskProf2, a parallelism profiler and an adviser for task parallel programs. As a parallelism profiler, TaskProf2 pinpoints regions with serialization bottlenecks, scheduling overheads, and secondary effects of execution. As an adviser, TaskProf2 identifies re…
We present ISymb an incremental symbolic inference framework for probabilistic programs in situations when some loop-manipulated array data, upon which their probabilistic models are conditioned, undergoes small changes. To tackle the path explosion challenge, ISymb is intra-proc…
We derive a variant of quantum Hoare logic (QHL), called applied quantum Hoare logic (aQHL for short), by: 1. restricting QHL to a special class of preconditions and postconditions, namely projections, which can significantly simplify verification of quantum programs and are much…
Despite the tremendous advances that have been made in the last decade on developing useful machine-learning applications, their wider adoption has been hindered by the lack of strong assurance guarantees that can be made about their behavior. In this paper, we consider how forma…
Predicting program properties such as names or expression types has a wide range of applications. It can ease the task of programming, and increase programmer productivity. A major challenge when learning from programs is how to represent programs in a way that facilitates effect…
A classic problem in parallel computing is to take a high-level parallel program written, for example, in nested-parallel style with fork-join constructs and run it efficiently on a real machine. The problem could be considered solved in theory, but not in practice, because the o…
State-of-the-art algorithms used in automatic polyhedral transformation for parallelization and locality optimization typically rely on Integer Linear Programming (ILP). This poses a scalability issue when scaling to tens or hundreds of statements, and may be disconcerting in pro…