{"title":"SecureMR","authors":"Yao Dong, Ana L. Milanova, Julian T Dolby","doi":"10.1145/3200691.3178520","DOIUrl":"https://doi.org/10.1145/3200691.3178520","url":null,"abstract":"In cloud computing customers upload data and computation to cloud providers. As they cede their data to the cloud provider, they may cede data confidentiality. We develop SecureMR, a system that analyzes and transforms MapReduce programs to operate over encrypted data. SecureMR makes use of partially homomorphic encryption and a trusted client. We evaluate SecureMR on a set of MapReduce benchmarks.","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":"59 1","pages":"389 - 390"},"PeriodicalIF":0.0,"publicationDate":"2018-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81442516","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}
{"title":"VerifiedFT","authors":"James R. Wilcox, C. Flanagan, Stephen N. Freund","doi":"10.1145/3200691.3178514","DOIUrl":"https://doi.org/10.1145/3200691.3178514","url":null,"abstract":"Dynamic data race detectors are valuable tools for testing and validating concurrent software, but to achieve good performance they are typically implemented using sophisticated concurrent algorithms. Thus, they are ironically prone to the exact same kind of concurrency bugs they are designed to detect. To address these problems, we have developed VerifiedFT, a clean slate redesign of the FastTrack race detector [19]. The VerifiedFT analysis provides the same precision guarantee as FastTrack, but is simpler to implement correctly and efficiently, enabling us to mechanically verify an implementation of its core algorithm using CIVL [27]. Moreover, VerifiedFT provides these correctness guarantees without sacrificing any performance over current state-of-the-art (but complex and unverified) FastTrack implementations for Java.","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":"29 1","pages":"354 - 367"},"PeriodicalIF":0.0,"publicationDate":"2018-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81643550","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}
{"title":"An effective fusion and tile size model for optimizing image processing pipelines","authors":"JangdaAbhinav, BondhugulaUday","doi":"10.1145/3200691.3178507","DOIUrl":"https://doi.org/10.1145/3200691.3178507","url":null,"abstract":"Effective models for fusion of loop nests continue to remain a challenge in both general-purpose and domain-specific language (DSL) compilers. The difficulty often arises from the combinatorial exp...","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3200691.3178507","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45732129","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}
{"title":"Griffin","authors":"Yang Liu, Jianguo Wang, S. Swanson","doi":"10.1145/3200691.3178512","DOIUrl":"https://doi.org/10.1145/3200691.3178512","url":null,"abstract":"Interactive information retrieval services, such as enterprise search and document search, must provide relevant results with consistent, low response times in the face of rapidly growing data sets and query loads. These growing demands have led researchers to consider a wide range of optimizations to reduce response latency, including query processing parallelization and acceleration with co-processors such as GPUs. However, previous work runs queries either on GPU or CPU, ignoring the fact that the best processor for a given query depends on the query's characteristics, which may change as the processing proceeds. We present Griffin, an IR systems that dynamically combines GPU- and CPU-based algorithms to process individual queries according to their characteristics. Griffin uses state-of-the-art CPU-based query processing techniques and incorporates a novel approach to GPU-based query evaluation. Our GPU-based approach, as far as we know, achieves the best available GPU search performance by leveraging a new compression scheme and exploiting an advanced merge-based intersection algorithm. We evaluate Griffin with real world queries and datasets, and show that it improves query performance by 10x compared to a highly optimized CPU-only implementation, and 1.5x compared to our GPU-approach running alone. We also find that Griffin helps reduce the 95th-, 99th-, and 99.9th-percentile query response time by 10.4x, 16.1x, and 26.8x, respectively.","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":"21 1","pages":"327 - 337"},"PeriodicalIF":0.0,"publicationDate":"2018-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87722768","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}
Da Zheng, Disa Mhembere, J. Vogelstein, Carey E. Priebe, R. Burns
{"title":"FlashR","authors":"Da Zheng, Disa Mhembere, J. Vogelstein, Carey E. Priebe, R. Burns","doi":"10.1145/3200691.3178501","DOIUrl":"https://doi.org/10.1145/3200691.3178501","url":null,"abstract":"R is one of the most popular programming languages for statistics and machine learning, but it is slow and unable to scale to large datasets. The general approach for having an efficient algorithm in R is to implement it in C or FORTRAN and provide an R wrapper. FlashR accelerates and scales existing R code by parallelizing a large number of matrix functions in the R base package and scaling them beyond memory capacity with solid-state drives (SSDs). FlashR performs memory hierarchy aware execution to speed up parallelized R code by (i) evaluating matrix operations lazily, (ii) performing all operations in a DAG in a single execution and with only one pass over data to increase the ratio of computation to I/O, (iii) performing two levels of matrix partitioning and reordering computation on matrix partitions to reduce data movement in the memory hierarchy. We evaluate FlashR on various machine learning and statistics algorithms on inputs of up to four billion data points. Despite the huge performance gap between SSDs and RAM, FlashR on SSDs closely tracks the performance of FlashR in memory for many algorithms. The R implementations in FlashR outperforms H2O and Spark MLlib by a factor of 3 -- 20.","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":"2 1","pages":"183 - 194"},"PeriodicalIF":0.0,"publicationDate":"2018-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82578379","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}
{"title":"Bounded expectations: resource analysis for probabilistic programs","authors":"V. Ngo, Quentin Carbonneaux, Jan Hoffmann","doi":"10.1145/3296979.3192394","DOIUrl":"https://doi.org/10.1145/3296979.3192394","url":null,"abstract":"This paper presents a new static analysis for deriving upper bounds on the expected resource consumption of probabilistic programs. The analysis is fully automatic and derives symbolic bounds that are multivariate polynomials in the inputs. The new technique combines manual state-of-the-art reasoning techniques for probabilistic programs with an effective method for automatic resource-bound analysis of deterministic programs. It can be seen as both, an extension of automatic amortized resource analysis (AARA) to probabilistic programs and an automation of manual reasoning for probabilistic programs that is based on weakest preconditions. An advantage of the technique is that it combines the clarity and compositionality of a weakest-precondition calculus with the efficient automation of AARA. As a result, bound inference can be reduced to off-the-shelf LP solving in many cases and automatically-derived bounds can be interactively extended with standard program logics if the automation fails. Building on existing work, the soundness of the analysis is proved with respect to an operational semantics that is based on Markov decision processes. The effectiveness of the technique is demonstrated with a prototype implementation that is used to automatically analyze 39 challenging probabilistic programs and randomized algorithms. Experiments indicate that the derived constant factors in the bounds are very precise and even optimal for some programs.","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":"3 1","pages":"496 - 512"},"PeriodicalIF":0.0,"publicationDate":"2017-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75584658","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}
{"title":"Program synthesis using conflict-driven learning","authors":"Yu Feng, R. Martins, O. Bastani, Işıl Dillig","doi":"10.1145/3296979.3192382","DOIUrl":"https://doi.org/10.1145/3296979.3192382","url":null,"abstract":"We propose a new conflict-driven program synthesis technique that is capable of learning from past mistakes. Given a spurious program that violates the desired specification, our synthesis algorithm identifies the root cause of the conflict and learns new lemmas that can prevent similar mistakes in the future. Specifically, we introduce the notion of equivalence modulo conflict and show how this idea can be used to learn useful lemmas that allow the synthesizer to prune large parts of the search space. We have implemented a general-purpose CDCL-style program synthesizer called Neo and evaluate it in two different application domains, namely data wrangling in R and functional programming over lists. Our experiments demonstrate the substantial benefits of conflict-driven learning and show that Neo outperforms two state-of-the-art synthesis tools, Morpheus and Deepcoder, that target these respective domains.","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":"23 1","pages":"420 - 435"},"PeriodicalIF":0.0,"publicationDate":"2017-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90242465","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}
{"title":"Refining semantics for multi-stage programming","authors":"Gerui, GarciaRonald","doi":"10.1145/3170492.3136047","DOIUrl":"https://doi.org/10.1145/3170492.3136047","url":null,"abstract":"The multi-stage programming paradigm supports runtime code generation and execution. Though powerful, its potential is impeded by the lack of static analysis support. Van Horn and Might proposed a ...","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3170492.3136047","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42768045","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}
{"title":"EffectiveSan: type and memory error detection using dynamically typed C/C++","authors":"Gregory J. Duck, R. Yap","doi":"10.1145/3192366.3192388","DOIUrl":"https://doi.org/10.1145/3192366.3192388","url":null,"abstract":"Low-level programming languages with weak/static type systems, such as C and C++, are vulnerable to errors relating to the misuse of memory at runtime, such as (sub-)object bounds overflows, (re)use-after-free, and type confusion. Such errors account for many security and other undefined behavior bugs for programs written in these languages. In this paper, we introduce the notion of dynamically typed C/C++, which aims to detect such errors by dynamically checking the \"effective type\" of each object before use at runtime. We also present an implementation of dynamically typed C/C++ in the form of the Effective Type Sanitizer (EffectiveSan). EffectiveSan enforces type and memory safety using a combination of low-fat pointers, type meta data and type/bounds check instrumentation. We evaluate EffectiveSan against the SPEC2006 benchmark suite and the Firefox web browser, and detect several new type and memory errors. We also show that EffectiveSan achieves high compatibility and reasonable overheads for the given error coverage. Finally, we highlight that EffectiveSan is one of only a few tools that can detect sub-object bounds errors, and uses a novel approach (dynamic type checking) to do so.","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":"23 1","pages":"181 - 195"},"PeriodicalIF":0.0,"publicationDate":"2017-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87553306","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}
MaurerLuke, DownenPaul, M. AriolaZena, P. JonesSimon
{"title":"Compiling without continuations","authors":"MaurerLuke, DownenPaul, M. AriolaZena, P. JonesSimon","doi":"10.1145/3140587.3062380","DOIUrl":"https://doi.org/10.1145/3140587.3062380","url":null,"abstract":"Many fields of study in compilers give rise to the concept of a join point—a place where different execution paths come together. Join points are often treated as functions or continuations, but we...","PeriodicalId":50923,"journal":{"name":"ACM Sigplan Notices","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2017-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3140587.3062380","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42936524","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}
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