Coz: Finding Code that Counts with Causal Profiling

Improving performance is a central concern for software developers. To locate optimization opportunities, developers rely on software profilers. However, these profilers only report where programs spent their time: optimizing that code may have no impact on performance. Past profilers thus both waste developer time and make it difficult for them to uncover significant optimization opportunities. This paper introduces causal profiling. Unlike past profiling approaches, causal profiling indicates exactly where programmers should focus their optimization efforts, and quantifies their potential impact. Causal profiling works by running performance experiments during program execution. Each experiment calculates the impact of any potential optimization by virtually speeding up code: inserting pauses that slow down all other code running concurrently. The key insight is that this slowdown has the same relative effect as running that line faster, thus "virtually" speeding it up. We present Coz, a causal profiler, which we evaluate on a range of highly-tuned applications: Memcached, SQLite, and the PARSEC benchmark suite. Coz identifies previously unknown optimization opportunities that are both significant and targeted. Guided by Coz, we improve the performance of Memcached by 9%, SQLite by 25%, and accelerate six PARSEC applications by as much as 68%; in most cases, these optimizations involve modifying under 10 lines of code.Comment: Published at SOSP 2015 (Best Paper Award

UC Berkeley's Cory Hall: Evaluation of Challenges and Potential Applications of Building-to-Grid Implementation

From September 2009 through June 2010, a team of researchers developed, installed, and tested instrumentation on the energy flows in Cory Hall on the UC Berkeley campus to create a Building-to-Grid testbed. The UC Berkeley team was headed by Professor David Culler, and assisted by members from EnerNex, Lawrence Berkeley National Laboratory, California State University Sacramento, and the California Institute for Energy & Environment. While the Berkeley team mapped the load tree of the building, EnerNex researched types of meters, submeters, monitors, and sensors to be used (Task 1). Next the UC Berkeley team analyzed building needs and designed the network of metering components and data storage/visualization software (Task 2). After meeting with vendors in January, the UCB team procured and installed the components starting in late March (Task 3). Next, the UCB team tested and demonstrated the system (Task 4). Meanwhile, the CSUS team documented the methodology and steps necessary to implement a testbed (Task 5) and Harold Galicer developed a roadmap for the CSUS Smart Grid Center with results from the testbed (Task 5a) and evaluated the Cory Hall implementation process (Task 5b). The CSUS team also worked with local utilities to develop an approach to the energy information communication link between buildings and the utility (Task 6). The UC Berkeley team then prepared a roadmap to outline necessary technology development for Building-to-Grid, and presented the results of the project in early July (Task 7). Finally, CIEE evaluated the implementation, noting challenges and potential applications of Building-to-Grid (Task 8). These deliverables are available at the i4Energy site: http://i4energy.org/

Fast and Precise Symbolic Analysis of Concurrency Bugs in Device Drivers

© 2015 IEEE.Concurrency errors, such as data races, make device drivers notoriously hard to develop and debug without automated tool support. We present Whoop, a new automated approach that statically analyzes drivers for data races. Whoop is empowered by symbolic pairwise lockset analysis, a novel analysis that can soundly detect all potential races in a driver. Our analysis avoids reasoning about thread interleavings and thus scales well. Exploiting the race-freedom guarantees provided by Whoop, we achieve a sound partial-order reduction that significantly accelerates Corral, an industrial-strength bug-finder for concurrent programs. Using the combination of Whoop and Corral, we analyzed 16 drivers from the Linux 4.0 kernel, achieving 1.5 - 20× speedups over standalone Corral

On capabilities and limitations of current fast neutron-flux monitoring instrumentation for the DEMO LFR ALFRED

Among Gen IV projects for future nuclear power plants, Lead cooled Fast Reactors (LFR) seem to be a very interesting solution due to its benefits in terms of fuel cycle, coolant-safety and waste management. The novelty of the matter causes some open issues about coolant chemical aspect, structural aspects, monitoring instrumentation, etc. Particularly hard neutron flux spectra would make traditional neutron instrumentation unfit to all reactor conditions, i.e. source, intermediate, and power range. Identification of new models of nuclear instrumentation specialized for LFR neutron flux monitoring asks for an accurate evaluation of the environment the sensor will work in. In this study, thermal-hydraulics and chemical conditions for LFR core environment will be assumed, as the neutron flux will be studied extensively by means of the Monte Carlo transport code MCNPX. The core coolant’s high temperature drastically reduces the candidate instrumentation, because only some kind of fission chambers and Self Powered Neutron Detectors can be operated in such an environment. This work aims at evaluating the capabilities of the available instrumentation (usually designed and tailored for Sodium cooled Fast Reactors, SFRs) when exposed to the neutron spectrum derived from ALFRED, a pool-type LFR project to demonstrate the feasibility of this technology into the European framework. This paper shows that such class of instrumentation does follow the power evolution, but is not completely suitable to detect the whole range of reactor power, due to excessive burn-up, damages or gamma interferences. Some improvements are possible in order to increase the signal-to-noise ratio, by optimizing each instrument in the range of reactor power, such to get the best solution. The design of some new detectors are here proposed, together with a possible approach for prototyping and testing them by means of a fast reactor

Waveform Approach for Assessing Conformity of CISPR 16-1-1 Measuring Receivers

An alternative approach for assessing the conformity of electromagnetic interference measuring receivers with respect to the baseline CISPR 16-1-1 requirements is proposed. The method’s core is based on the generation of digitally synthesized complex waveforms comprising multisine excitation signals and modulated pulses. The superposition of multiple narrowband reference signals populating the standard frequency bands allows for a single-stage evaluation of the receiver’s voltage accuracy and frequency selectivity. Moreover, characterizing the response of the weighting detectors using modulated pulses is more repeatable and less restrictive than the conventional approach. This methodology significantly reduces the amount of time required to complete the verification of the receiver’s baseline magnitudes, because time-domain measurements enable a broadband assessment while the typical calibration methodology follows the time-consuming narrow band frequency sweep scheme. Since the reference signals are generated using arbitrary waveform generators, they can be easily reproduced from a standard numerical vector. For different test receivers, the results of such assessment are presented in the 9 kHz–1 GHz frequency range. Finally, a discussion on the measurement uncertainty of this methodology for assessing measuring receivers is given.Postprint (author's final draft

Smart driving aids and their effects on driving performance and driver distraction

In-vehicle information systems have been shown to increase driver workload and cause distraction; both of which are causal factors for accidents. This simulator study evaluates the impact that two designs for a smart driving aid, and scenario complexity have on workload, distraction and driving performance. Results showed that real-time delivery of smart driving information did not increase driver workload or adversely effect driver distraction, while having the effect of decreasing mean driving speed in both the simple and complex driving scenarios. Subjective workload was shown to increase with task difficulty, as well as revealing important differences between the two interface designs

Modelling transport energy demand : a socio-technical approach

Peer reviewedPostprin

Service quality measurements for IPv6 inter-networks

Measurement-based performance evaluation of network traffic is becoming very important, especially for networks trying to provide differentiated levels of service quality to the different application flows. The non-identical response of flows to the different types of network-imposed performance degradation raises the need for ubiquitous measurement mechanisms, able to measure numerous performance properties, and being equally applicable to different applications and transports. This paper presents a new measurement mechanism, facilitated by the steady introduction of IPv6 in network nodes and hosts, which exploits native features of the protocol to provide support for performance measurements at the network (IP) layer. IPv6 Extension Headers have been used to carry the triggers involving the measurement activity and the measurement data in-line with the payload data itself, providing a high level of probability that the behaviour of the real user traffic flows is observed. End-to-end one-way delay, jitter, loss, and throughput have been measured for applications operating on top of both reliable and unreliable transports, over different-capacity IPv6 network configurations. We conclude that this technique could form the basis for future Internet measurements that can be dynamically deployed where and when required in a multi-service IP environment