Yizhou Zhang, G. Salvaneschi, Quinn Beightol, B. Liskov, A. Myers
Unhandled exceptions crash programs, so a compile-time check that exceptions are handled should in principle make software more reliable. But designers of some recent languages have argued that the benefits of statically checked exceptions are not worth the costs. We introduce a new statically checked exception mechanism that addresses the problems with existing checked-exception mechanisms. In particular, it interacts well with higher-order functions and other design patterns. The key insight is that whether an exception should be treated as a "checked" exception is not a property of its type but rather of the context in which the exception propagates. Statically checked exceptions can "tunnel" through code that is oblivious to their presence, but the type system nevertheless checks that these exceptions are handled. Further, exceptions can be tunneled without being accidentally caught, by expanding the space of exception identifiers to identify the exception-handling context. The resulting mechanism is expressive and syntactically light, and can be implemented efficiently. We demonstrate the expressiveness of the mechanism using significant codebases and evaluate its performance. We have implemented this new exception mechanism as part of the new Genus programming language, but the mechanism could equally well be applied to other programming languages.
{"title":"Accepting blame for safe tunneled exceptions","authors":"Yizhou Zhang, G. Salvaneschi, Quinn Beightol, B. Liskov, A. Myers","doi":"10.1145/2908080.2908086","DOIUrl":"https://doi.org/10.1145/2908080.2908086","url":null,"abstract":"Unhandled exceptions crash programs, so a compile-time check that exceptions are handled should in principle make software more reliable. But designers of some recent languages have argued that the benefits of statically checked exceptions are not worth the costs. We introduce a new statically checked exception mechanism that addresses the problems with existing checked-exception mechanisms. In particular, it interacts well with higher-order functions and other design patterns. The key insight is that whether an exception should be treated as a \"checked\" exception is not a property of its type but rather of the context in which the exception propagates. Statically checked exceptions can \"tunnel\" through code that is oblivious to their presence, but the type system nevertheless checks that these exceptions are handled. Further, exceptions can be tunneled without being accidentally caught, by expanding the space of exception identifiers to identify the exception-handling context. The resulting mechanism is expressive and syntactically light, and can be implemented efficiently. We demonstrate the expressiveness of the mechanism using significant codebases and evaluate its performance. We have implemented this new exception mechanism as part of the new Genus programming language, but the mechanism could equally well be applied to other programming languages.","PeriodicalId":178839,"journal":{"name":"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122774644","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}
Web computing is gradually shifting toward mobile devices, in which the energy budget is severely constrained. As a result, Web developers must be conscious of energy efficiency. However, current Web languages provide developers little control over energy consumption. In this paper, we take a first step toward language-level research to enable energy-efficient Web computing. Our key motivation is that mobile systems can wisely budget energy usage if informed with user quality-of-service (QoS) constraints. To do this, programmers need new abstractions. We propose two language abstractions, QoS type and QoS target, to capture two fundamental aspects of user QoS experience. We then present GreenWeb, a set of language extensions that empower developers to easily express the QoS abstractions as program annotations. As a proof of concept, we develop a GreenWeb runtime, which intelligently determines how to deliver specified user QoS expectation while minimizing energy consumption. Overall, GreenWeb shows significant energy savings (29.2% ∼ 66.0%) over Android’s default Interactive governor with few QoS violations. Our work demonstrates a promising first step toward language innovations for energy-efficient Web computing.
{"title":"GreenWeb: language extensions for energy-efficient mobile web computing","authors":"Yuhao Zhu, V. Reddi","doi":"10.1145/2908080.2908082","DOIUrl":"https://doi.org/10.1145/2908080.2908082","url":null,"abstract":"Web computing is gradually shifting toward mobile devices, in which the energy budget is severely constrained. As a result, Web developers must be conscious of energy efficiency. However, current Web languages provide developers little control over energy consumption. In this paper, we take a first step toward language-level research to enable energy-efficient Web computing. Our key motivation is that mobile systems can wisely budget energy usage if informed with user quality-of-service (QoS) constraints. To do this, programmers need new abstractions. We propose two language abstractions, QoS type and QoS target, to capture two fundamental aspects of user QoS experience. We then present GreenWeb, a set of language extensions that empower developers to easily express the QoS abstractions as program annotations. As a proof of concept, we develop a GreenWeb runtime, which intelligently determines how to deliver specified user QoS expectation while minimizing energy consumption. Overall, GreenWeb shows significant energy savings (29.2% ∼ 66.0%) over Android’s default Interactive governor with few QoS violations. Our work demonstrates a promising first step toward language innovations for energy-efficient Web computing.","PeriodicalId":178839,"journal":{"name":"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125889059","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}
O. Padon, K. McMillan, Aurojit Panda, Shmuel Sagiv, Sharon Shoham
Despite several decades of research, the problem of formal verification of infinite-state systems has resisted effective automation. We describe a system --- Ivy --- for interactively verifying safety of infinite-state systems. Ivy's key principle is that whenever verification fails, Ivy graphically displays a concrete counterexample to induction. The user then interactively guides generalization from this counterexample. This process continues until an inductive invariant is found. Ivy searches for universally quantified invariants, and uses a restricted modeling language. This ensures that all verification conditions can be checked algorithmically. All user interactions are performed using graphical models, easing the user's task. We describe our initial experience with verifying several distributed protocols.
{"title":"Ivy: safety verification by interactive generalization","authors":"O. Padon, K. McMillan, Aurojit Panda, Shmuel Sagiv, Sharon Shoham","doi":"10.1145/2908080.2908118","DOIUrl":"https://doi.org/10.1145/2908080.2908118","url":null,"abstract":"Despite several decades of research, the problem of formal verification of infinite-state systems has resisted effective automation. We describe a system --- Ivy --- for interactively verifying safety of infinite-state systems. Ivy's key principle is that whenever verification fails, Ivy graphically displays a concrete counterexample to induction. The user then interactively guides generalization from this counterexample. This process continues until an inductive invariant is found. Ivy searches for universally quantified invariants, and uses a restricted modeling language. This ensures that all verification conditions can be checked algorithmically. All user interactions are performed using graphical models, easing the user's task. We describe our initial experience with verifying several distributed protocols.","PeriodicalId":178839,"journal":{"name":"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130844487","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}
By abstracting away the complexity of distributed systems, large-scale data processing platforms—MapReduce, Hadoop, Spark, Dryad, etc.—have provided developers with simple means for harnessing the power of the cloud. In this paper, we ask whether we can automatically synthesize MapReduce-style distributed programs from input–output examples. Our ultimate goal is to enable end users to specify large-scale data analyses through the simple interface of examples. We thus present a new algorithm and tool for synthesizing programs composed of efficient data-parallel operations that can execute on cloud computing infrastructure. We evaluate our tool on a range of real-world big-data analysis tasks and general computations. Our results demonstrate the efficiency of our approach and the small number of examples it requires to synthesize correct, scalable programs.
{"title":"MapReduce program synthesis","authors":"Calvin Smith, Aws Albarghouthi","doi":"10.1145/2908080.2908102","DOIUrl":"https://doi.org/10.1145/2908080.2908102","url":null,"abstract":"By abstracting away the complexity of distributed systems, large-scale data processing platforms—MapReduce, Hadoop, Spark, Dryad, etc.—have provided developers with simple means for harnessing the power of the cloud. In this paper, we ask whether we can automatically synthesize MapReduce-style distributed programs from input–output examples. Our ultimate goal is to enable end users to specify large-scale data analyses through the simple interface of examples. We thus present a new algorithm and tool for synthesizing programs composed of efficient data-parallel operations that can execute on cloud computing infrastructure. We evaluate our tool on a range of real-world big-data analysis tasks and general computations. Our results demonstrate the efficiency of our approach and the small number of examples it requires to synthesize correct, scalable programs.","PeriodicalId":178839,"journal":{"name":"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127445629","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}
Prefix sums are an important parallel primitive, especially in massively-parallel programs. This paper discusses two orthogonal generalizations thereof, which we call higher-order and tuple-based prefix sums. Moreover, it describes and evaluates SAM, a GPU-friendly algorithm for computing prefix sums and other scans that directly supports higher orders and tuple values. Its templated CUDA implementation unifies all of these computations in a single 100-statement kernel. SAM is communication-efficient in the sense that it minimizes main-memory accesses. When computing prefix sums of a million or more values, it outperforms Thrust and CUDPP on both a Titan X and a K40 GPU. On the Titan X, SAM reaches memory-copy speeds for large input sizes, which cannot be surpassed. SAM outperforms CUB, the currently fastest conventional prefix sum implementation, by up to a factor of 2.9 on eighth-order prefix sums and by up to a factor of 2.6 on eight-tuple prefix sums.
{"title":"Higher-order and tuple-based massively-parallel prefix sums","authors":"Sepideh Maleki, Annie Yang, Martin Burtscher","doi":"10.1145/2908080.2908089","DOIUrl":"https://doi.org/10.1145/2908080.2908089","url":null,"abstract":"Prefix sums are an important parallel primitive, especially in massively-parallel programs. This paper discusses two orthogonal generalizations thereof, which we call higher-order and tuple-based prefix sums. Moreover, it describes and evaluates SAM, a GPU-friendly algorithm for computing prefix sums and other scans that directly supports higher orders and tuple values. Its templated CUDA implementation unifies all of these computations in a single 100-statement kernel. SAM is communication-efficient in the sense that it minimizes main-memory accesses. When computing prefix sums of a million or more values, it outperforms Thrust and CUDPP on both a Titan X and a K40 GPU. On the Titan X, SAM reaches memory-copy speeds for large input sizes, which cannot be surpassed. SAM outperforms CUB, the currently fastest conventional prefix sum implementation, by up to a factor of 2.9 on eighth-order prefix sums and by up to a factor of 2.6 on eight-tuple prefix sums.","PeriodicalId":178839,"journal":{"name":"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":"93 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126137525","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}
Ulan Degenbaev, J. Eisinger, M. Ernst, R. McIlroy, H. Payer
Efficient garbage collection is increasingly important in today's managed language runtime systems that demand low latency, low memory consumption, and high throughput. Garbage collection may pause the application for many milliseconds to identify live memory, free unused memory, and compact fragmented regions of memory, even when employing concurrent garbage collection. In animation-based applications that require 60 frames per second, these pause times may be observable, degrading user experience. This paper introduces idle time garbage collection scheduling to increase the responsiveness of applications by hiding expensive garbage collection operations inside of small, otherwise unused idle portions of the application's execution, resulting in smoother animations. Additionally we take advantage of idleness to reduce memory consumption while allowing higher memory use when high throughput is required. We implemented idle time garbage collection scheduling in V8, an open-source, production JavaScript virtual machine running within Chrome. We present performance results on various benchmarks running popular webpages and show that idle time garbage collection scheduling can significantly improve latency and memory consumption. Furthermore, we introduce a new metric called frame time discrepancy to quantify the quality of the user experience and precisely measure the improvements that idle time garbage collection provides for a WebGL-based game benchmark. Idle time garbage collection is shipped and enabled by default in Chrome.
{"title":"Idle time garbage collection scheduling","authors":"Ulan Degenbaev, J. Eisinger, M. Ernst, R. McIlroy, H. Payer","doi":"10.1145/2908080.2908106","DOIUrl":"https://doi.org/10.1145/2908080.2908106","url":null,"abstract":"Efficient garbage collection is increasingly important in today's managed language runtime systems that demand low latency, low memory consumption, and high throughput. Garbage collection may pause the application for many milliseconds to identify live memory, free unused memory, and compact fragmented regions of memory, even when employing concurrent garbage collection. In animation-based applications that require 60 frames per second, these pause times may be observable, degrading user experience. This paper introduces idle time garbage collection scheduling to increase the responsiveness of applications by hiding expensive garbage collection operations inside of small, otherwise unused idle portions of the application's execution, resulting in smoother animations. Additionally we take advantage of idleness to reduce memory consumption while allowing higher memory use when high throughput is required. We implemented idle time garbage collection scheduling in V8, an open-source, production JavaScript virtual machine running within Chrome. We present performance results on various benchmarks running popular webpages and show that idle time garbage collection scheduling can significantly improve latency and memory consumption. Furthermore, we introduce a new metric called frame time discrepancy to quantify the quality of the user experience and precisely measure the improvements that idle time garbage collection provides for a WebGL-based game benchmark. Idle time garbage collection is shipped and enabled by default in Chrome.","PeriodicalId":178839,"journal":{"name":"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124961099","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}
Over the past 5-10 years, the rise of software-defined networking (SDN) has inspired a wide range of new systems, libraries, hypervisors and languages for programming, monitoring, and debugging network behavior. Oftentimes, these systems are disjoint—one language for programming and another for verification, and yet another for run-time monitoring and debugging. In this paper, we present a new, unified framework, called Temporal NetKAT, capable of facilitating all of these tasks at once. As its name suggests, Temporal NetKAT is the synthesis of two formal theories: past-time (finite trace) linear temporal logic and (network) Kleene Algebra with Tests. Temporal predicates allow programmers to write down concise properties of a packet’s path through the network and to make dynamic packet-forwarding, access control or debugging decisions on that basis. In addition to being useful for programming, the combined equational theory of LTL and NetKAT facilitates proofs of path-based correctness properties. Using new, general, proof techniques, we show that the equational semantics is sound with respect to the denotational semantics, and, for a class of programs we call network-wide programs, complete. We have also implemented a compiler for temporal NetKAT, evaluated its performance on a range of benchmarks, and studied the effectiveness of several optimizations.
{"title":"Temporal NetKAT","authors":"Ryan Beckett, M. Greenberg, D. Walker","doi":"10.1145/2908080.2908108","DOIUrl":"https://doi.org/10.1145/2908080.2908108","url":null,"abstract":"Over the past 5-10 years, the rise of software-defined networking (SDN) has inspired a wide range of new systems, libraries, hypervisors and languages for programming, monitoring, and debugging network behavior. Oftentimes, these systems are disjoint—one language for programming and another for verification, and yet another for run-time monitoring and debugging. In this paper, we present a new, unified framework, called Temporal NetKAT, capable of facilitating all of these tasks at once. As its name suggests, Temporal NetKAT is the synthesis of two formal theories: past-time (finite trace) linear temporal logic and (network) Kleene Algebra with Tests. Temporal predicates allow programmers to write down concise properties of a packet’s path through the network and to make dynamic packet-forwarding, access control or debugging decisions on that basis. In addition to being useful for programming, the combined equational theory of LTL and NetKAT facilitates proofs of path-based correctness properties. Using new, general, proof techniques, we show that the equational semantics is sound with respect to the denotational semantics, and, for a class of programs we call network-wide programs, complete. We have also implemented a compiler for temporal NetKAT, evaluated its performance on a range of benchmarks, and studied the effectiveness of several optimizations.","PeriodicalId":178839,"journal":{"name":"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131061674","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}
We present the systematic design of a testing environment that uses stressing and fuzzing to reveal errors in GPU applications that arise due to weak memory effects. We evaluate our approach on seven GPUs spanning three Nvidia architectures, across ten CUDA applications that use fine-grained concurrency. Our results show that applications that rarely or never exhibit errors related to weak memory when executed natively can readily exhibit these errors when executed in our testing environment. Our testing environment also provides a means to help identify the root causes of such errors, and automatically suggests how to insert fences that harden an application against weak memory bugs. To understand the cost of GPU fences, we benchmark applications with fences provided by the hardening strategy as well as a more conservative, sound fencing strategy.
{"title":"Exposing errors related to weak memory in GPU applications","authors":"Tyler Sorensen, A. Donaldson","doi":"10.1145/2908080.2908114","DOIUrl":"https://doi.org/10.1145/2908080.2908114","url":null,"abstract":"We present the systematic design of a testing environment that uses stressing and fuzzing to reveal errors in GPU applications that arise due to weak memory effects. We evaluate our approach on seven GPUs spanning three Nvidia architectures, across ten CUDA applications that use fine-grained concurrency. Our results show that applications that rarely or never exhibit errors related to weak memory when executed natively can readily exhibit these errors when executed in our testing environment. Our testing environment also provides a means to help identify the root causes of such errors, and automatically suggests how to insert fences that harden an application against weak memory bugs. To understand the cost of GPU fences, we benchmark applications with fences provided by the hardening strategy as well as a more conservative, sound fencing strategy.","PeriodicalId":178839,"journal":{"name":"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114729265","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}
Junghyun Kim, Gangwon Jo, Jaehoon Jung, Jungwon Kim, Jaejin Lee
Applications written solely in OpenCL or CUDA cannot execute on a cluster as a whole. Most previous approaches that extend these programming models to clusters are based on a common idea: designating a centralized host node and coordinating the other nodes with the host for computation. However, the centralized host node is a serious performance bottleneck when the number of nodes is large. In this paper, we propose a scalable and distributed OpenCL framework called SnuCL-D for large-scale clusters. SnuCL-D's remote device virtualization provides an OpenCL application with an illusion that all compute devices in a cluster are confined in a single node. To reduce the amount of control-message and data communication between nodes, SnuCL-D replicates the OpenCL host program execution and data in each node. We also propose a new OpenCL host API function and a queueing optimization technique that significantly reduce the overhead incurred by the previous centralized approaches. To show the effectiveness of SnuCL-D, we evaluate SnuCL-D with a microbenchmark and eleven benchmark applications on a large-scale CPU cluster and a medium-scale GPU cluster.
{"title":"A distributed OpenCL framework using redundant computation and data replication","authors":"Junghyun Kim, Gangwon Jo, Jaehoon Jung, Jungwon Kim, Jaejin Lee","doi":"10.1145/2908080.2908094","DOIUrl":"https://doi.org/10.1145/2908080.2908094","url":null,"abstract":"Applications written solely in OpenCL or CUDA cannot execute on a cluster as a whole. Most previous approaches that extend these programming models to clusters are based on a common idea: designating a centralized host node and coordinating the other nodes with the host for computation. However, the centralized host node is a serious performance bottleneck when the number of nodes is large. In this paper, we propose a scalable and distributed OpenCL framework called SnuCL-D for large-scale clusters. SnuCL-D's remote device virtualization provides an OpenCL application with an illusion that all compute devices in a cluster are confined in a single node. To reduce the amount of control-message and data communication between nodes, SnuCL-D replicates the OpenCL host program execution and data in each node. We also propose a new OpenCL host API function and a queueing optimization technique that significantly reduce the overhead incurred by the previous centralized approaches. To show the effectiveness of SnuCL-D, we evaluate SnuCL-D with a microbenchmark and eleven benchmark applications on a large-scale CPU cluster and a medium-scale GPU cluster.","PeriodicalId":178839,"journal":{"name":"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122644623","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}
Stefan Heule, Eric Schkufza, Rahul Sharma, A. Aiken
The x86-64 ISA sits at the bottom of the software stack of most desktop and server software. Because of its importance, many software analysis and verification tools depend, either explicitly or implicitly, on correct modeling of the semantics of x86-64 instructions. However, formal semantics for the x86-64 ISA are difficult to obtain and often written manually through great effort. We describe an automatically synthesized formal semantics of the input/output behavior for a large fraction of the x86-64 Haswell ISA’s many thousands of instruction variants. The key to our results is stratified synthesis, where we use a set of instructions whose semantics are known to synthesize the semantics of additional instructions whose semantics are unknown. As the set of formally described instructions increases, the synthesis vocabulary expands, making it possible to synthesize the semantics of increasingly complex instructions. Using this technique we automatically synthesized formal semantics for 1,795 instruction variants of the x86-64 Haswell ISA. We evaluate the learned semantics against manually written semantics (where available) and find that they are formally equivalent with the exception of 50 instructions, where the manually written semantics contain an error. We further find the learned formulas to be largely as precise as manually written ones and of similar size.
{"title":"Stratified synthesis: automatically learning the x86-64 instruction set","authors":"Stefan Heule, Eric Schkufza, Rahul Sharma, A. Aiken","doi":"10.1145/2908080.2908121","DOIUrl":"https://doi.org/10.1145/2908080.2908121","url":null,"abstract":"The x86-64 ISA sits at the bottom of the software stack of most desktop and server software. Because of its importance, many software analysis and verification tools depend, either explicitly or implicitly, on correct modeling of the semantics of x86-64 instructions. However, formal semantics for the x86-64 ISA are difficult to obtain and often written manually through great effort. We describe an automatically synthesized formal semantics of the input/output behavior for a large fraction of the x86-64 Haswell ISA’s many thousands of instruction variants. The key to our results is stratified synthesis, where we use a set of instructions whose semantics are known to synthesize the semantics of additional instructions whose semantics are unknown. As the set of formally described instructions increases, the synthesis vocabulary expands, making it possible to synthesize the semantics of increasingly complex instructions. Using this technique we automatically synthesized formal semantics for 1,795 instruction variants of the x86-64 Haswell ISA. We evaluate the learned semantics against manually written semantics (where available) and find that they are formally equivalent with the exception of 50 instructions, where the manually written semantics contain an error. We further find the learned formulas to be largely as precise as manually written ones and of similar size.","PeriodicalId":178839,"journal":{"name":"Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123246374","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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