Runtime Automated Detection of Out of Process Resource Management in the X Windowing System

Software applications typically allocate and deallocate resources during their lifetime. Resources can be categorized into two broad groups, in-process and out-of-process resources where in-process resources are local resources directly managed by a client, while out-of-process resources are remotely managed by a client which instructs a server to allocate and deallocate the resource on its behalf. Out-of-process resources do not reside in a clients address space which poses an extra layer of complexity in attempting to debug their misuse. This thesis presents an automatic run-time solution to the problem of detecting and reporting source code locations of application client mismanagement of out-of-process resources for a specific case-study of the X Windowing System which lends itself to use in the wider general case

Memory and I/O optimized rectilinear steiner minimum tree routing for VLSI

As the size of devices are scaling down at rapid pace, the interconnect delay play a major part in performance of IC chips. Therefore minimizing delay and wire length is the most desired objective. FLUTE (Fast Look-Up table) presented a fast and accurate RSMT (Rectilinear Steiner Minimum Tree) construction for both smaller and higher degree net. FLUTE presented an optimization technique that reduces time complexity for RSMT construction for both smaller and larger degree nets. However for larger degree net this technique induces memory overhead, as it does not consider the memory requirement in constructing RSMT. Since availability of memory is very less and is expensive, it is desired to utilize memory more efficiently which in turn results in reducing I/O time (i.e. reduce the number of I/O disk access). The proposed work presents a Memory Optimized RSMT (MORSMT) construction in order to address the memory overhead for larger degree net. The depth-first search and divide and conquer approach is adopted to build a Memory optimized tree. Experiments are conducted to evaluate the performance of proposed approach over existing model for varied benchmarks in terms of computation time, memory overhead and wire length. The experimental results show that the proposed model is scalable and efficient

Governing with Insights: Towards Profile-Driven Cache Management of Black-Box Applications

There exists a divide between the ever-increasing demand for high-performance embedded systems and the availability of practical methodologies to understand the interplay of complex data-intensive applications with hardware memory resources. On the one hand, traditional static analysis approaches are seldomly applicable to latest-generation multi-core platforms due to a lack of accurate micro-architectural models. On the other hand, measurement-based methods only provide coarse-grained information about the end-to-end execution of a given real-time application. In this paper, we describe a novel methodology, namely Black-Box Profiling (BBProf), to gather fine-grained insights on the usage of cache resources in applications of realistic complexity. The goal of our technique is to extract the relative importance of individual memory pages towards the overall temporal behavior of a target application. Importantly, BBProf does not require the semantics of the target application to be known - i.e., applications are treated as black-boxes - and it does not rely on any platform-specific hardware support. We provide an open-source full-system implementation and showcase how BBProf can be used to perform profile-driven cache management

MadT: A Memory Access Detection Tool for Symbolic Memory Profiling

Tools for memory access detection are widely used, playing an important role especially in real-time systems. For example, on multi-core platforms, the problem of co-scheduling CPU and memory resources with hard real-time constraints requires a deep understanding of the memory access patterns of the deployed taskset. While code execution flow can be analyzed by considering the control-flow graph and reasoning in terms of basic blocks, a similar approach cannot apply to data accesses. In this paper, we propose MadT, a tool that uses a novel mechanism to perform memory access detection of general purpose applications. MadT does not perform binary instrumentation and always executes application code natively on the platform. Hence it can operate entirely in user-space without sand-boxing the task under analysis. Furthermore, MadT provides detailed symbolic information about the accessed memory structures, so it is able to translate the virtual addresses to their original symbolic variable names. Finally, it requires no modifications to application source code. The proposed methodology relies on existing OS-level capabilities. In this paper, we describe how MadT can be implemented on commercial hardware and we compare its performance with state-of-the-art software techniques for memory access detection.CNS-1302563CNS-1219064Ope

08441 Abstracts Collection -- Emerging Uses and Paradigms for Dynamic Binary Translation

From 26.10. to 31.10.2008, the Dagstuhl Seminar 08441 ``Emerging Uses and Paradigms for Dynamic Binary Translation \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Detecting and escaping infinite loops with jolt

25th European Conference, Lancaster, Uk, July 25-29, 2011 ProceedingsInfinite loops can make applications unresponsive. Potential problems include lost work or output, denied access to application functionality, and a lack of responses to urgent events. We present Jolt, a novel system for dynamically detecting and escaping infinite loops. At the user’s request, Jolt attaches to an application to monitor its progress. Specifically, Jolt records the program state at the start of each loop iteration. If two consecutive loop iterations produce the same state, Jolt reports to the user that the application is in an infinite loop. At the user’s option, Jolt can then transfer control to a statement following the loop, thereby allowing the application to escape the infinite loop and ideally continue its productive execution. The immediate goal is to enable the application to execute long enough to save any pending work, finish any in-progress computations, or respond to any urgent events. We evaluated Jolt by applying it to detect and escape eight infinite loops in five benchmark applications. Jolt was able to detect seven of the eight infinite loops (the eighth changes the state on every iteration). We also evaluated the effect of escaping an infinite loop as an alternative to terminating the application. In all of our benchmark applications, escaping an infinite loop produced a more useful output than terminating the application. Finally, we evaluated how well escaping from an infinite loop approximated the correction that the developers later made to the application. For two out of our eight loops, escaping the infinite loop produced the same output as the corrected version of the application