Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation最新文献_第6页

Reverse engineering for reduction parallelization via semiring polynomials 通过半环多项式减少并行化的逆向工程

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation Pub Date : 2021-06-18 DOI: 10.1145/3453483.3454079

Akimasa Morihata, Shigeyuki Sato

{"title":"Reverse engineering for reduction parallelization via semiring polynomials","authors":"Akimasa Morihata, Shigeyuki Sato","doi":"10.1145/3453483.3454079","DOIUrl":"https://doi.org/10.1145/3453483.3454079","url":null,"abstract":"Parallel reduction, which summarizes a given dataset, e.g., the total, average, and maximum, plays a crucial role in parallel programming. This paper presents a new approach, reverse engineering, to automatically discovering nontrivial parallel reductions in sequential programs. The body of the sequential reduction loop is regarded as a black box, and its input-output behaviors are sampled. If the behaviors correspond to a set of linear polynomials over a semiring, a divide-and-conquer parallel reduction is generated. Auxiliary reverse-engineering methods enable a long and nested loop body to be decomposed, which makes our parallelization scheme applicable to various types of reduction loops. This approach is not only simple and efficient but also agnostic to the details of the input program. Its potential is demonstrated through several use case scenarios. A proof-of-concept implementation successfully inferred linear polynomials for nearly all of the 74 benchmarks exhaustively collected from the literature. These characteristics and experimental results demonstrate the promise of the proposed approach, despite its inherent unsoundness.","PeriodicalId":20557,"journal":{"name":"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82153456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Mirror: making lock-free data structures persistent 镜像:使无锁的数据结构持久化

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation Pub Date : 2021-06-18 DOI: 10.1145/3453483.3454105

Michal Friedman, E. Petrank, P. Ramalhete

{"title":"Mirror: making lock-free data structures persistent","authors":"Michal Friedman, E. Petrank, P. Ramalhete","doi":"10.1145/3453483.3454105","DOIUrl":"https://doi.org/10.1145/3453483.3454105","url":null,"abstract":"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 complex and error-prone as caches and machine registers are still volatile and the data residing in memory after a crash might not reflect a consistent view of the program state. This complex setting has often led to durable data structures being inefficient or incorrect, especially in the concurrent setting. In this paper, we present Mirror -- a simple, general automatic transformation that adds durability to lock-free data structures, with a low performance overhead. Moreover, in the current non-volatile main memory configuration, where non-volatile memory operates side-by-side with a standard fast DRAM, our mechanism exploits the hybrid system to substantially improve performance. Evaluation shows a significant performance advantage over NVTraverse, which is the state-of-the-art general transformation technique, and over Intel's concurrent lock-based key-value datastore. Unlike some previous transformations, Mirror does not require any restriction on the lock-free data structure format.","PeriodicalId":20557,"journal":{"name":"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89420465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 29

When threads meet events: efficient and precise static race detection with origins 当线程遇到事件时:具有起源的高效和精确的静态竞争检测

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation Pub Date : 2021-06-18 DOI: 10.1145/3453483.3454073

Bozhen Liu, Peiming Liu, Yanze Li, Chia-che Tsai, Dilma Da Silva, Jeff Huang

{"title":"When threads meet events: efficient and precise static race detection with origins","authors":"Bozhen Liu, Peiming Liu, Yanze Li, Chia-che Tsai, Dilma Da Silva, Jeff Huang","doi":"10.1145/3453483.3454073","DOIUrl":"https://doi.org/10.1145/3453483.3454073","url":null,"abstract":"Data races are among the worst bugs in software in that they exhibit non-deterministic symptoms and are notoriously difficult to detect. The problem is exacerbated by interactions between threads and events in real-world applications. We present a novel static analysis technique, O2, to detect data races in large complex multithreaded and event-driven software. O2 is powered by “origins”, an abstraction that unifies threads and events by treating them as entry points of code paths attributed with data pointers. Origins in most cases are inferred automatically, but can also be specified by developers. More importantly, origins provide an efficient way to precisely reason about shared memory and pointer aliases. Together with several important design choices for race detection, we have implemented O2 for both C/C++ and Java/Android applications and applied it to a wide range of open-source software. O2 has found new races in every single real-world code base we evaluated with, including Linux kernel, Redis, OVS, Memcached, Hadoop, Tomcat, ZooKeeper and Firefox Android. Moreover, O2 scales to millions of lines of code in a few minutes, on average 70x faster (up to 568x) compared to an existing static analysis tool from our prior work, and reduces false positives by 77%. We also compared O2 with the state-of-the-art static race detection tool, RacerD, showing highly promising results. At the time of writing, O2 has revealed more than 40 unique previously unknown races that have been confirmed or fixed by developers.","PeriodicalId":20557,"journal":{"name":"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75262899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Transfinite Iris: resolving an existential dilemma of step-indexed separation logic 超限虹膜:解决阶梯索引分离逻辑的存在困境

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation Pub Date : 2021-06-18 DOI: 10.1145/3453483.3454031

Simon Spies, Lennard Gäher, Daniel Gratzer, Joseph Tassarotti, R. Krebbers, Derek Dreyer, L. Birkedal

引用次数: 11

Compiling Stan to generative probabilistic languages and extension to deep probabilistic programming 将Stan编译为生成概率语言，并扩展到深度概率规划

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation Pub Date : 2021-06-15 DOI: 10.1145/3453483.3454058

Guillaume Baudart, Javier Burroni, Martin Hirzel, Louis Mandel, Avraham Shinnar

引用次数: 6

Example-guided synthesis of relational queries 以示例为指导的关系查询合成

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation Pub Date : 2021-06-15 DOI: 10.1145/3453483.3454098

Aalok Thakkar, Aaditya Naik, Nathaniel Sands, R. Alur, M. Naik, Mukund Raghothaman

引用次数: 14

An efficient interpreter for Datalog by de-specializing relations 通过去专门化关系实现对Datalog的高效解释器

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation Pub Date : 2021-06-15 DOI: 10.1145/3453483.3454070

Xiaowen Hu, David Zhao, Herbert Jordan, Bernhard Scholz

引用次数: 1

Hashing modulo alpha-equivalence 哈希模等价

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation Pub Date : 2021-05-06 DOI: 10.1145/3453483.3454088

Krzysztof Maziarz, Tom Ellis, A. Lawrence, A. Fitzgibbon, S. Jones

引用次数: 3

Vectorized secure evaluation of decision forests 决策林的矢量化安全评价

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation Pub Date : 2021-04-19 DOI: 10.1145/3453483.3454094

Raghav Malik, Vidushi Singhal, Benjamin Gottfried, Milind Kulkarni

{"title":"Vectorized secure evaluation of decision forests","authors":"Raghav Malik, Vidushi Singhal, Benjamin Gottfried, Milind Kulkarni","doi":"10.1145/3453483.3454094","DOIUrl":"https://doi.org/10.1145/3453483.3454094","url":null,"abstract":"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 data being leaked. Fully Homomorphic Encryption (FHE) allows arbitrary computation to be done over encrypted data, providing an attractive approach to providing such secure inference. While such computation is often orders of magnitude slower than its plaintext counterpart, the ability of FHE cryptosystems to do ciphertext packing—that is, encrypting an entire vector of plaintexts such that operations are evaluated elementwise on the vector—helps ameliorate this overhead, effectively creating a SIMD architecture where computation can be vectorized for more efficient evaluation. Most recent research in this area has targeted regular, easily vectorizable neural network models. Applying similar techniques to irregular ML models such as decision forests remains unexplored, due to their complex, hard-to-vectorize structures. In this paper we present COPSE, the first system that exploits ciphertext packing to perform decision-forest inference. COPSE consists of a staging compiler that automatically restructures and compiles decision forest models down to a new set of vectorizable primitives for secure inference. We find that COPSE’s compiled models outperform the state of the art across a range of decision forest models, often by more than an order of magnitude, while still scaling well.","PeriodicalId":20557,"journal":{"name":"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74410402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Automated conformance testing for JavaScript engines via deep compiler fuzzing 通过深度编译器模糊测试对JavaScript引擎进行自动化一致性测试

Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation Pub Date : 2021-04-15 DOI: 10.1145/3453483.3454054

Guixin Ye, Zhanyong Tang, Shin Hwei Tan, Songfang Huang, Dingyi Fang, Xiaoyang Sun, Lizhong Bian, Haibo Wang, Zheng Wang

{"title":"Automated conformance testing for JavaScript engines via deep compiler fuzzing","authors":"Guixin Ye, Zhanyong Tang, Shin Hwei Tan, Songfang Huang, Dingyi Fang, Xiaoyang Sun, Lizhong Bian, Haibo Wang, Zheng Wang","doi":"10.1145/3453483.3454054","DOIUrl":"https://doi.org/10.1145/3453483.3454054","url":null,"abstract":"JavaScript (JS) is a popular, platform-independent programming language. To ensure the interoperability of JS programs across different platforms, the implementation of a JS engine should conform to the ECMAScript standard. However, doing so is challenging as there are many subtle definitions of API behaviors, and the definitions keep evolving. We present COMFORT, a new compiler fuzzing framework for detecting JS engine bugs and behaviors that deviate from the ECMAScript standard. COMFORT leverages the recent advance in deep learning-based language models to automatically generate JS test code. As a departure from prior fuzzers, COMFORT utilizes the well-structured ECMAScript specifications to automatically generate test data along with the test programs to expose bugs that could be overlooked by the developers or manually written test cases. COMFORT then applies differential testing methodologies on the generated test cases to expose standard conformance bugs. We apply COMFORT to ten mainstream JS engines. In 200 hours of automated concurrent testing runs, we discover bugs in all tested JS engines. We had identified 158 unique JS engine bugs, of which 129 have been verified, and 115 have already been fixed by the developers. Furthermore, 21 of the COMFORT-generated test cases have been added to Test262, the official ECMAScript conformance test suite.","PeriodicalId":20557,"journal":{"name":"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84626938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 41