We present PIDGIN, a program analysis and understanding tool that enables the specification and enforcement of precise application-specific information security guarantees. PIDGIN also allows developers to interactive...
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ISBN:
(纸本)9781450334686
We present PIDGIN, a program analysis and understanding tool that enables the specification and enforcement of precise application-specific information security guarantees. PIDGIN also allows developers to interactively explore the information flows in their applications to develop policies and investigate counter-examples. PIDGIN combines program dependence graphs (PDGs), which precisely capture the information flows in a whole application, with a custom PDG query language. Queries express properties about the paths in the PDG;because paths in the PDG correspond to information flows in the application, queries can be used to specify global security policies. PIDGIN is scalable. Generating a PDG for a 330k line Java application takes 90 seconds, and checking a policy on that PDG takes under 14 seconds. The query language is expressive, supporting a large class of precise, application-specific security guarantees. Policies are separate from the code and do not interfere with testing or development, and can be used for security regression testing. We describe the design and implementation of PIDGIN and report on using it: (1) to explore information security guarantees in legacy programs;(2) to develop and modify security policies concurrently with application development;and (3) to develop policies based on known vulnerabilities.
Rapid exploration of the design space with simulation models is essential for quality hardware systems research and development. Despite striking commonalities across hardware systems, designers routinely fail to achi...
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Rapid exploration of the design space with simulation models is essential for quality hardware systems research and development. Despite striking commonalities across hardware systems, designers routinely fail to achieve high levels of reuse across models constructed in existing general-purpose and domain-specific languages. This lack of reuse adversely impacts hardware system design by slowing the rate at which ideas are evaluated. This paper presents an examination of existing languages to reveal their fundamental limitations regarding reuse in hardware modeling. With this understanding, a solution is described in the context of the design and implementation of the Liberty Structural Specification language (LSS), the input language for a publicly available high-level digital-hardware modeling tool called the Liberty Simulation Environment. LSS is the first language to enable low-overhead reuse by simultaneously supporting static inference based on hardware structure and flexibility via parameterizable structure. Through LSS, this paper also introduces a new type inference algorithm and a new programminglanguage technique, called use-based specialization, which, in a manner analogous to type inference, customizes reusable components by statically inferring structural properties that otherwise would have had to have been specified manually.
Energy harvesting enables novel devices and applications without batteries, but intermittent operation under energy harvesting poses new challenges to memory consistency that threaten to leave applications in failed s...
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ISBN:
(纸本)9781450334686
Energy harvesting enables novel devices and applications without batteries, but intermittent operation under energy harvesting poses new challenges to memory consistency that threaten to leave applications in failed states not reachable in continuous execution. This paper presents analytical models that aid in reasoning about intermittence. Using these, we develop DINO (Death Is Not an Option), a programming and execution model that simplifies programming for intermittent systems and ensures volatile and nonvolatile data consistency despite near-constant interruptions. DINO is the first system to address these consistency problems in the context of intermittent execution. We evaluate DINO on three energy-harvesting hardware platforms running different applications. The applications fail and exhibit error without DINO, but run correctly with DINO's modest 1.8-2.7x run-time overhead. DINO also dramatically simplifies programming, reducing the set of possible failure-related control transfers by 5-9x.
作者：
Wu, YFIntel Labs
Programming Syst Res Santa Clara CA 95052 USA
Irregular data references are difficult to prefetch, as the future memory address of a load instruction is hard to anticipate by a compiler. However, recent studies as well as our experience indicate that some importa...
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Irregular data references are difficult to prefetch, as the future memory address of a load instruction is hard to anticipate by a compiler. However, recent studies as well as our experience indicate that some important load instructions in irregular programs contain stride access patterns. Although the load instructions with stride patterns are difficult to identify with static compiler techniques, we developed an efficient profiling method to discover these load instructions. The new profiling method integrates the profiling for stride information and the traditional profiling for edge frequency into a single profiling pass. The integrated profiling pass runs only 17% slower than the frequency profiling alone. The collected stride information helps the compiler to identify load instructions with stride patterns that can be prefetched efficiently and beneficially. We implemented the new profiling and prefetching techniques in a research compiler for Itanium(TM) Processor Family (IPF), and obtained significant performance improvement for the SPECINT2000 programs running on Itanium machines. For example, we achieved a 1.59x speedup for *** 1.14x for ***, and 1.08x for ***. We also showed that the performance gain is stable across input data sets. These benefits make the new profiling and prefetching techniques suitable for production compilers.
Image processing pipelines combine the challenges of stencil computations and stream programs. They are composed of large graphs of different stencil stages, as well as complex reductions, and stages with global or da...
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ISBN:
(纸本)9781450320146
Image processing pipelines combine the challenges of stencil computations and stream programs. They are composed of large graphs of different stencil stages, as well as complex reductions, and stages with global or data-dependent access patterns. Because of their complex structure, the performance difference between a naive implementation of a pipeline and an optimized one is often an order of magnitude. Efficient implementations require optimization of both parallelism and locality, but due to the nature of stencils, there is a fundamental tension between parallelism, locality, and introducing redundant recomputation of shared values. We present a systematic model of the tradeoff space fundamental to stencil pipelines, a schedule representation which describes concrete points in this space for each stage in an image processing pipeline, and an optimizing compiler for the Halide image processing language that synthesizes high performance implementations from a Halide algorithm and a schedule. Combining this compiler with stochastic search over the space of schedules enables terse, composable programs to achieve state-of-the-art performance on a wide range of real image processing pipelines, and across different hardware architectures, including multicores with SIMD, and heterogeneous CPU+GPU execution. From simple Halide programs written in a few hours, we demonstrate performance up to 5x faster than hand-tuned C, intrinsics, and CUDA implementations optimized by experts over weeks or months, for image processing applications beyond the reach of past automatic compilers.
programming concurrent, distributed systems is hard-especially when these systems mutate shared, persistent state replicated at geographic scale. To enable high availability and scalability, a new class of weakly cons...
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ISBN:
(纸本)9781450356985
programming concurrent, distributed systems is hard-especially when these systems mutate shared, persistent state replicated at geographic scale. To enable high availability and scalability, a new class of weakly consistent data stores has become popular. However, some data needs strong consistency. To manipulate both weakly and strongly consistent data in a single transaction, we introduce a new abstraction: mixed-consistency transactions, embodied in a new embedded language, MixT. Programmers explicitly associate consistency models with remote storage sites;each atomic, isolated transaction can access a mixture of data with different consistency models. Compile-time information-flow checking, applied to consistency models, ensures that these models are mixed safely and enables the compiler to automatically partition transactions. New run-time mechanisms ensure that consistency models can also be mixed safely, even when the data used by a transaction resides on separate, mutually unaware stores. Performance measurements show that despite their stronger guarantees, mixed-consistency transactions retain much of the speed of weak consistency, significantly outperforming traditional serializable transactions.
Dynamic class loading during program execution in the Java(TM) programminglanguage is an impediment for generating code that is as efficient as code generated using static whole-program analysis and optimization. Who...
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Dynamic class loading during program execution in the Java(TM) programminglanguage is an impediment for generating code that is as efficient as code generated using static whole-program analysis and optimization. Whole-program analysis and optimization is possible for languages, such as C++, that do not allow new classes and/or methods to be loaded during program execution. One solution for performing whole-program analysis and avoiding incorrect execution after a new class is loaded is to invalidate and recompile affected methods. Runtime invalidation and recompilation mechanisms can be expensive in both space and time, and, therefore, generally restrict optimization. To address these drawbacks, we propose a new framework, called the errant analysis framework, for interprocedural optimization of programs that support dynamic class (or method) loading. Given a set of classes comprising the closed world, we perform an offline static analysis which partitions references into two categories: (1) unconditionally extant references which point only to objects whose runtime type is guaranteed to be in the closed world;and (2) conditionally extant references which point to objects whose runtime type is not guaranteed to be in the closed world. Optimizations solely dependent on the first category can be statically performed, and are guaranteed to be correct even with any future class/method loading. Optimizations dependent on the second category are guarded by dynamic tests, called extane safety tests, for correct execution behavior. We describe the properties for extant safety tests, and provide algorithms for their generation and placement.
We present associated effects, a programminglanguage feature that enables type classes to abstract over the effects of their function signatures, allowing each type class instance to specify its concrete effects. Ass...
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We present associated effects, a programminglanguage feature that enables type classes to abstract over the effects of their function signatures, allowing each type class instance to specify its concrete effects. Associated effects significantly increase the flexibility and expressive power of a programminglanguage that combines a type and effect system with type classes. In particular, associated effects allow us to (i) abstract over total and partial functions, where partial functions may throw exceptions, (ii) abstract over immutable data structures and mutable data structures that have heap effects, and (iii) implement adaptors that combine type classes with algebraic effects. We implement associated effects as an extension of the Flix programminglanguage and refactor the Flix Standard Library to use associated effects, significantly increasing its flexibility and expressive power. Specifically, we add associated effects to 11 type classes, which enables us to add 28 new type class instances.
Over the last five years, graphics cards have become a tempting target for scientific computing, thanks to unrivaled peak performance, often producing a runtime speed-up of x10 to x25 over comparable CPU solutions. Ho...
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ISBN:
(纸本)9781450312059
Over the last five years, graphics cards have become a tempting target for scientific computing, thanks to unrivaled peak performance, often producing a runtime speed-up of x10 to x25 over comparable CPU solutions. However, this increase can be difficult to achieve, and doing so often requires a fundamental rethink. This is especially problematic in scientific computing, where experts do not want to learn yet another architecture. In this paper we develop a method for automatically parallelising recursive functions of the sort found in scientific papers. Using a static analysis of the function dependencies we identify sets - partitions - of independent elements, which we use to synthesise an efficient GPU implementation using polyhedral code generation techniques. We then augment our language with DSL extensions to support a wider variety of applications, and demonstrate the effectiveness of this with three case studies, showing significant performance improvement over equivalent CPU methods, and similar efficiency to hand-tuned GPU implementations.
As computation becomes increasingly limited by data movement and energy consumption, exploiting locality throughout the memory hierarchy becomes critical for maintaining the performance scaling that many have come to ...
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