Energy versus data integrity trade-offs in embedded high-density logic compatible dynamic memories

Current variation aware design methodologies, tuned for worst-case scenarios, are becoming increasingly pessimistic from the perspective of power and performance. A good example of such pessimism is setting the refresh rate of DRAMs according to the worst-case access statistics, thereby resulting in very frequent refresh cycles, which are responsible for the majority of the standby power consumption of these memories. However, such a high refresh rate may not be required, either due to extremely low probability of the actual occurrence of such a worst-case, or due to the inherent error resilient nature of many applications that can tolerate a certain number of potential failures. In this paper, we exploit and quantify the possibilities that exist in dynamic memory design by shifting to the so-called approximate computing paradigm in order to save power and enhance yield at no cost. The statistical characteristics of the retention time in dynamic memories were revealed by studying a fabricated 2kb CMOS compatible embedded DRAM (eDRAM) memory array based on gain-cells. Measurements show that up to 73% of the retention power can be saved by altering the refresh time and setting it such that a small number of failures is allowed. We show that these savings can be further increased by utilizing known circuit techniques, such as body biasing, which can help, not only in extending, but also in preferably shaping the retention time distribution. Our approach is one of the first attempts to access the data integrity and energy tradeoffs achieved in eDRAMs for utilizing them in error resilient applications and can prove helpful in the anticipated shift to approximate computing.

Executing bag of distributed tasks on the cloud: Investigating the trade-offs between performance and cost

Bag of Distributed Tasks (BoDT) can benefit from decentralised execution on the Cloud. However, there is a trade-off between the performance that can be achieved by employing a large number of Cloud VMs for the tasks and the monetary constraints that are often placed by a user. The research reported in this paper is motivated towards investigating this trade-off so that an optimal plan for deploying BoDT applications on the cloud can be generated. A heuristic algorithm, which considers the user's preference of performance and cost is proposed and implemented. The feasibility of the algorithm is demonstrated by generating execution plans for a sample application. The key result is that the algorithm generates optimal execution plans for the application over 91% of the time.

Robust Room Temperature Hysteresis in an FeIII Spin Crossover Metallomesogen

The high temperature magnetic and structural properties of an amphiphilic iron(III) spin crossover complex are reported. Thermal cycling reveals a scan rate-dependent 20 K thermal hysteresis in the mT vs. T data close to room temperature. A fast scan rate is essential for the hysteresis but it is robust and reproducible after multiple thermal cycles. Differential scanning calorimetry and cross polarized microscopy are used to show that the magnetic switching aligns with a material state change from solid to ordered liquid phase on warming.

Do exoplanets spin up their host stars?

We have collected initial evidence that tidal interaction between a late-type star and its close-in, massive planet can lead to a spin-up of the host star. We propose to explore this further by studying a small sample of proper motion pairs in which one of the stars is orbited by a Hot Jupiter. We will determine if the activity-estimated age appears to be strongly different for the two stars, which would indicate a tidal spin up of the Hot Jupiter host star. We propose to observe 4 such systems with Chandra/ACIS-S, and to perform a similar observation of one additional system with large angular separation using XMM-Newton/EPIC. The total proposed exposure times are 141 ks (Chandra) and 38 ks (XMM).

The Rossiter-McLaughlin effect reloaded: Probing the 3D spin-orbit geometry, differential stellar rotation, and the spatially-resolved stellar spectrum of star-planet systems

When a planet transits its host star, it blocks regions of the stellar surface from view; this causes a distortion of the spectral lines and a change in the line-of-sight (LOS) velocities, known as the Rossiter-McLaughlin (RM) effect. Since the LOS velocities depend, in part, on the stellar rotation, the RM waveform is sensitive to the star-planet alignment (which provides information on the system’s dynamical history). We present a new RM modelling technique that directly measures the spatially-resolved stellar spectrum behind the planet. This is done by scaling the continuum flux of the (HARPS) spectra by the transit light curve, and then subtracting the infrom the out-of-transit spectra to isolate the starlight behind the planet. This technique does not assume any shape for the intrinsic local profiles. In it, we also allow for differential stellar rotation and centre-to-limb variations in the convective blueshift. We apply this technique to HD 189733 and compare to 3D magnetohydrodynamic (MHD) simulations. We reject rigid body rotation with high confidence (>99% probability), which allows us to determine the occulted stellar latitudes and measure the stellar inclination. In turn, we determine both the sky-projected (λ ≈ −0.4 ± 0.2◦) and true 3D obliquity (ψ ≈ 7+12 −4 ◦ ). We also find good agreement with the MHD simulations, with no significant centre-to-limb variations detectable in the local profiles. Hence, this technique provides a new powerful tool that can probe stellar photospheres, differential rotation, determine 3D obliquities, and remove sky-projection biases in planet migration theories. This technique can be implemented with existing instrumentation, but will become even more powerful with the next generation of high-precision radial velocity spectrographs.

The Effect of Seat Location in Lecture Theatres on Academic Performance

The purpose of this research study was to investigate and identify possible patterns relating to academic performance on the effects of university students self-selecting where to sit in a lecture theatre.
The key research questions are:
1. Does seating position affect student performance?
2. Do the most academically able and engaged students regularly sit at the front of lecture theatres?
Academic achievement
Preliminary results suggest significant assessment score differences between those that sit at the front and those that sit further the back. Of those that received a grade of 75%+ (Grade A) 6.67% regularly sat at the back. With the same group 46.67% regularly sat at the front. Of the group that scored less than 50% (Grade D) 0% of students regularly sat at the front. 12.50% regularly sat in the middle zones with 37.50% sitting at the back. It was also observed that the remaining numbers did not consistently sit in the same zone.

Temporal movement
There is little evidence of movement between seating zones of the Grade A group throughout the 24 week period. However there was considerable movement with the Grade D group. Although still under analysis there appears be a pattern of students in this group graduating towards the back seating positions over the course of the programme.

Engagement
The frequency of completed entries on PinPoint was also used as an indicator of engagement. With the Grade A group 75% of them regularly completed an entry whereas in the Grade D group this drops to less than 50%.
Further analysis on the attitudinal factors in relational to seating position and performance are ongoing, but preliminary results suggest that those students that scored highly in attitude tended to sit at the front and middle sections.
It would indeed appear that the more highly engaged and academically capable students voluntarily sit at the front for most lectures. Interestingly as the course progresses those who had lesser engagement and below average midterm results tend to began to sit progressively toward the back. If this is a repeatable pattern then a linear regression analysis of the seating positions and midterm results could help predict students in danger of failing.