Coding for Phase Change Memory Performance Optimization

Over the past several decades, memory technologies have exploited continual scaling of CMOS to drastically improve performance and cost. Unfortunately, charge-based memories become unreliable beyond 20 nm feature sizes. A promising alternative is Phase-Change-Memory (PCM) which leverages scalable resistive thermal mechanisms. To realize PCM's potential, a number of challenges, including the limited wear-endurance and costly writes, need to be addressed. This thesis introduces novel methodologies for encoding data on PCM which exploit asymmetries in read/write performance to minimize memory's wear/energy consumption. First, we map the problem to a distance-based graph clustering problem and prove it is NP-hard. Next, we propose two different approaches: an optimal solution based on Integer-Linear-Programming, and an approximately-optimal solution based on Dynamic-Programming. Our methods target both single-level and multi-level cell PCM and provide further optimizations for stochastically-distributed data. We devise a low overhead hardware architecture for the encoder. Evaluations demonstrate significant performance gains of our framework

Hybrid heterogeneous energy supply networks

Abstract—Efficient energy supply, storage, and distribution are key technical challenges for design and operation of electronic systems. In particular, energy supply is the most scarce resource and constraint for mobile embedded systems where the supply lifetime, cost, weight, size, and portability are major concerns. With the advent of newer electrical energy supply and storage technologies, energy supplies with differing energy/power storage densities, cost, size, and recycling abilities are becoming available. Efficient system design requires an exact matching between the fluctuating load demands and the underlying energy resources. Combining the energy supplies in a hierarchical way creates a unique opportunity for efficient matching and variable load serving. Such a heterogeneous hybrid network of energy supply components could address a variety of power needs and serve a much broader range of system loads with a high efficiency. This paper presents a Hierarchial Architecture of Heterogenous Electrical Energy Supplies (HierArcHEES) that can be tuned to different load demands. I

Correlation of serum uric acid and proteinuria in patients with type 2 diabetes mellitus

Background: Diabetes mellitus is one of the most common and important metabolic diseases worldwide. Hperuricemia is associated with kidney damage manifested by glomerular hypertrophy and sclerosis. The aim of this study was evaluation of association between serum uric acid level and proteinuria in patients with type 2 diabetes mellitus. Methods: A total of 140 patients (48 men and 92 women) with type 2 diabetes mellitus were enrolled in the study. Demographic criteria as age, body mass index, serum uric acid level and 24 hours urine protein were measured in these patients. Finding: Mean of patients age was 59.8 ± 10 years. Uric acid level in patients with significant proteinuria (≥ 500 mg/24 h) and mild proteinuria (< 500 mg/24 h) were 6.70 ± 1.82 and 5.06 ± 1.46 mg/dl respectively (P < 0.001). Serum uric acid level had positive correlation with 24 hours urine protein, duration of diabetes and insulin treatment. Conclusion: In type 2 diabetes mellitus, serum uric acid level has positive correlation with proteinuria; so uric acid maybe has a role in progression of diabetic nephropathy

Exploring How Cognitive Differences Impact Behavior and Performance in The Face of IT Interruptions

While IT interruptions have improved users’ performance in the workplace and everyday life by providing them with timely information, numerous studies have reported their negative effects on users’ performance and behavior. In an attempt to understand how users’ cognitive capabilities affect their performance and behavior in the face of IT interruptions, we propose that the three main executive capabilities of users’ brains (Inhibition, Updating, Shifting) predict distinct performance and behavioral outcomes. The Inhibition capability predicts the likelihood that users get distracted by irrelevant IT interruptions while it improves their performance on the main task. Updating and Shifting capabilities positively impact users’ performance on both the interrupting and the main tasks. An experiment is designed where users are observed while performing a primary task while being interrupted by two types of IT interruptions (relevant versus irrelevant). Potential contributions are discussed