The hydrophilicity of polymers, as indicated by their swelling characteristics in water, is an important parameter with regard to their use as coatings which are able to modify the wettability and adhesive properties of a material. We have investigated the swelling behavior of a series of hydrophilic random copolymer coatings in controlled humidity environments and in water. Swelling data were obtained from a quartz crystal microbalance (QCM) and from spectroscopic ellipsometry. The hydrophilic polymers are based on polyacrylates with low molecular weight side chains of poly(ethylene glycol) (PEG). These polymers also contain a random distribution of acrylic acid. Triblock copolymers with these random copolymers as the midblock and poly(methyl methacrylate) (PMMA) as the end blocks have also been investigated. At low and intermediate humidities, the swelling behavior of appropriately chosen block copolymers is similar to the swelling behavior of the corresponding polymers that do not have the PMMA end blocks. Substantial differences between the two types of polymers are observed at very high humidities and in water. The PMMA end blocks stabilize the structure of the copolymer layer so that it does not dissolve in water. Swelling curves obtained from the quartz crystal microbalance and from ellipsometry are in agreement with one another when the shape of the quartz crystal resonance (as determined by impedance spectroscopy) is not affected by humidity. We also find evidence for a reversible, humidity-induced phase transition which is readily detectable by the quartz crystal microbalance.

This paper presents user-level dynamic page migration, a runtime technique which transparently enables parallel programs to tune their memory performance on distributed shared memory multiprocessors, with feedback obtained from dynamic monitoring of memory activity. Our technique exploits the iterative nature of parallel programs and information available to the program both at compile time and at runtime in order to improve the accuracy and the timeliness of page migrations, as well as amortize better the overhead, compared to page migration engines implemented in the operating system. We present an adaptive page migration algorithm based on a competitive and a predictive criterion. The competitive criterion is used to correct poor page placement decisions of the operating system, while the predictive criterion makes the algorithm responsive to scheduling events that necessitate immediate page migrations, such as preemptions and migrations of threads. We also present a new technique for preventing page pingpong and a mechanism for monitoring the performance of page migration algorithms at runtime and tuning their sensitive parameters accordingly. Our experimental evidence on a SGI Origin2000 shows that unmodified OpenMP codes linked with our runtime system for dynamic page migration are effectively immune to the page placement strategy of the operating system and the associated problems with data locality. Furthermore, our runtime system achieves solid performance improvements compared to the IRIX 6.5.5 page migration engine, for single parallel OpenMP codes and multiprogrammed workloads.

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This paper investigates the performance implications of data placement in OpenMP programs running on modern ccNUMA multiprocessors. Data locality and minimization of the rate of remote memory accesses are critical for sustaining high performance on these systems. We show that due to the low remote-to-local memory access latency ratio of state-of-the-art ccNUMA architectures, reasonably balanced page placement schemes, such as round-robin or random distribution of pages incur modest performance losses. We also show that performance leaks stemming from suboptimal page placement schemes can be remedied with a smart user-level page migration engine. The main body of the paper describes how the OpenMP runtime environment can use page migration for implementing implicit data distribution and redistribution schemes without programmer intervention. Our experimental results support the effectiveness of these mechanisms and provide a proof of concept that there is no need to introduce data distribution directives in OpenMP and warrant the portability of the programming model.

In this paper we reformulate the thread scheduling problem on multiprogrammed SMPs. Scheduling algorithms usually attempt to maximize performance of memory intensive applications by optimally exploiting the cache hierarchy. We present experimental results indicating that-contrary to the common belief-the extent of performance loss of memory-intensive, multiprogrammed workloads is disproportionate to the deterioration of cache performance caused by interference between threads. In previous work [1] we found that memory bandwidth saturation is often the actual bottleneck that determines the performance of multiprogrammed workloads. Therefore, we present and evaluate two realistic scheduling policies which treat memory bandwidth as a first-class resource. Their design methodology is general enough and can be applied to introduce bus bandwidth-awareness to conventional scheduling policies. Experimental results substantiate the advantages of our approach.