Chemistry and biology of DNA-binding small molecules

Regulation of the transcription machinery is one of the many ways to achieve control of gene expression. This has been done either at the transcription initiation stage or at the elongation stage. Different methodologies are known to inhibit transcription initiation via targeting of double-stranded (ds) DNA by: (i) synthetic oligonucleotides, (ii) ds-DNA-specific, sequenceselective minor-groove binders (distamycin A), intercalators (daunomycin) combilexins and (iii) small molecule (peptide or intercalator)-oligonucleotide conjugates. In some cases, instead of ds-DNA, higher order G-quadruplex structures are formed at the start site of transcription. In this regard G-quadruplex DNA-specific small molecules play a significant role towards inhibition of the transcription machinery. Different types of designer DNA-binding agents act as powerful sequence-specific gene modulators, by exerting their effect from transcription regulation to gene modification. But most of these chemotherapeutic agents have serious side effects. Accordingly, there is always a challenge to design such DNA-binding molecules that should not only achieve maximum specific DNA-binding affinity, and cellular and nuclear transport activity, but also would not interfere with the functions of normal cells.

Theory and Algorithms for Hop-Count-Based Localization with Random Geometric Graph Models of Dense Sensor Networks

Wireless sensor networks can often be viewed in terms of a uniform deployment of a large number of nodes in a region of Euclidean space. Following deployment, the nodes self-organize into a mesh topology with a key aspect being self-localization. Having obtained a mesh topology in a dense, homogeneous deployment, a frequently used approximation is to take the hop distance between nodes to be proportional to the Euclidean distance between them. In this work, we analyze this approximation through two complementary analyses. We assume that the mesh topology is a random geometric graph on the nodes; and that some nodes are designated as anchors with known locations. First, we obtain high probability bounds on the Euclidean distances of all nodes that are h hops away from a fixed anchor node. In the second analysis, we provide a heuristic argument that leads to a direct approximation for the density function of the Euclidean distance between two nodes that are separated by a hop distance h. This approximation is shown, through simulation, to very closely match the true density function. Localization algorithms that draw upon the preceding analyses are then proposed and shown to perform better than some of the well-known algorithms present in the literature. Belief-propagation-based message-passing is then used to further enhance the performance of the proposed localization algorithms. To our knowledge, this is the first usage of message-passing for hop-count-based self-localization.

Interplay of software bloat, hardware energy proportionality and system bottlenecks

In large flexible software systems, bloat occurs in many forms, causing excess resource utilization and resource bottlenecks. This results in lost throughput and wasted joules. However, mitigating bloat is not easy; efforts are best applied where savings would be substantial. To aid this we develop an analytical model establishing the relation between bottleneck in resources, bloat, performance and power. Analyses with the model places into perspective results from the first experimental study of the power-performance implications of bloat. In the experiments we find that while bloat reduction can provide as much as 40% energy savings, the degree of impact depends on hardware and software characteristics. We confirm predictions from our model with selected results from our experimental study. Our findings show that a software-only view is inadequate when assessing the effects of bloat. The impact of bloat on physical resource usage and power should be understood for a full systems perspective to properly deploy bloat reduction solutions and reap their power-performance benefits.

ReadAlong: reading articles and comments together

We propose a new paradigm for displaying comments: showing comments alongside parts of the article they correspond to. We evaluate the effectiveness of various approaches for this task and show that a combination of bag of words and topic models performs the best.

Extended histories: improving regularity and performance in correlation prefetchers

Data Prefetchers identify and make use of any regularity present in the history/training stream to predict future references and prefetch them into the cache. The training information used is typically the primary misses seen at a particular cache level, which is a filtered version of the accesses seen by the cache. In this work we demonstrate that extending the training information to include secondary misses and hits along with primary misses helps improve the performance of prefetchers. In addition to empirical evaluation, we use the information theoretic metric entropy, to quantify the regularity present in extended histories. Entropy measurements indicate that extended histories are more regular than the default primary miss only training stream. Entropy measurements also help corroborate our empirical findings. With extended histories, further benefits can be achieved by triggering prefetches during secondary misses also. In this paper we explore the design space of extended prefetch histories and alternative prefetch trigger points for delta correlation prefetchers. We observe that different prefetch schemes benefit to a different extent with extended histories and alternative trigger points. Also the best performing design point varies on a per-benchmark basis. To meet these requirements, we propose a simple adaptive scheme that identifies the best performing design point for a benchmark-prefetcher combination at runtime. In SPEC2000 benchmarks, using all the L2 accesses as history for prefetcher improves the performance in terms of both IPC and misses reduced over techniques that use only primary misses as history. The adaptive scheme improves the performance of CZone prefetcher over Baseline by 4.6% on an average. These performance gains are accompanied by a moderate reduction in the memory traffic requirements.

Loop transformations: convexity, pruning, and optimization

High-level loop transformations are a key instrument in mapping computational kernels to effectively exploit the resources in modern processor architectures. Nevertheless, selecting required compositions of loop transformations to achieve this remains a significantly challenging task; current compilers may be off by orders of magnitude in performance compared to hand-optimized programs. To address this fundamental challenge, we first present a convex characterization of all distinct, semantics-preserving, multidimensional affine transformations. We then bring together algebraic, algorithmic, and performance analysis results to design a tractable optimization algorithm over this highly expressive space. Our framework has been implemented and validated experimentally on a representative set of benchmarks running on state-of-the-art multi-core platforms.

Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset

In the design of practical web page classification systems one often encounters a situation in which the labeled training set is created by choosing some examples from each class; but, the class proportions in this set are not the same as those in the test distribution to which the classifier will be actually applied. The problem is made worse when the amount of training data is also small. In this paper we explore and adapt binary SVM methods that make use of unlabeled data from the test distribution, viz., Transductive SVMs (TSVMs) and expectation regularization/constraint (ER/EC) methods to deal with this situation. We empirically show that when the labeled training data is small, TSVM designed using the class ratio tuned by minimizing the loss on the labeled set yields the best performance; its performance is good even when the deviation between the class ratios of the labeled training set and the test set is quite large. When the labeled training data is sufficiently large, an unsupervised Gaussian mixture model can be used to get a very good estimate of the class ratio in the test set; also, when this estimate is used, both TSVM and EC/ER give their best possible performance, with TSVM coming out superior. The ideas in the paper can be easily extended to multi-class SVMs and MaxEnt models.

Biomechanics of Substrate Boring by Fig Wasps: Role of Zinc in Insect Cuticle

There are many biomechanical challenges that a female insect must meet to successfully oviposit and ensure her evolutionary success. These begin with selection of a suitable substrate through which the ovipositor must penetrate without itself buckling or fracturing. The second phase corresponds to steering and manipulating the ovipositor to deliver eggs at desired locations. Finally, the insect must retract her ovipositor fast to avoid possible predation and repeat this process multiple times during her lifetime. From a materials perspective, insect oviposition is a fascinating problem and poses many questions. Specifically, are there diverse mechanisms that insects use to drill through hard substrates without itself buckling or fracturing? What are the structure-property relationships in the ovipositor material? These are some of the questions we address with a model system consisting of a parasitoid fig wasp - fig substrate system. To characterize the structure of ovipositors, we use scanning electron microscopy with a detector to quantify the presence of transition elements. Our results show that parasitoid ovipositors have teeth like structures on their tips and contain high amounts of zinc as compared to remote regions. Sensillae are present along the ovipositor to aid detection of chemical species and mechanical deformations. To quantify the material properties of parasitoid ovipositors, we use an atomic force microscope and show that tip regions have higher modulus as compared to remote regions. Finally, we use videography to show that ovipositors buckle during oviposition and estimate the forces needed to cause substrate boring based on Euler buckling analysis. Such methods may be useful for the design of functionally graded surgical tools.

Processing of DNA double-stranded breaks and intermediates of recombination and repair by saccharomyces cerevisiae Mre11 and its stimulation by Rad50, Xrs2, and Sae2 proteins

Saccharomyces cerevisiae RAD50, MRE11, and XRS2 genes are essential for telomere length maintenance, cell cycle checkpoint signaling, meiotic recombination, and DNA double-stranded break (DSB) repair via nonhomologous end joining and homologous recombination. The DSB repair pathways that draw upon Mre11-Rad50-Xrs2 subunits are complex, so their mechanistic features remain poorly understood. Moreover, the molecular basis of DSB end resection in yeast mre11-nuclease deficient mutants and Mre11 nuclease-independent activation of ATM in mammals remains unknown and adds a new dimension to many unanswered questions about the mechanism of DSB repair. Here, we demonstrate that S. cerevisiae Mre11 (ScMre11) exhibits higher binding affinity for single-over double-stranded DNA and intermediates of recombination and repair and catalyzes robust unwinding of substrates possessing a 3' single-stranded DNA overhang but not of 5' overhangs or blunt-ended DNA fragments. Additional evidence disclosed that ScMre11 nuclease activity is dispensable for its DNA binding and unwinding activity, thus uncovering the molecular basis underlying DSB end processing in mre11 nuclease deficient mutants. Significantly, Rad50, Xrs2, and Sae2 potentiate the DNA unwinding activity of Mre11, thus underscoring functional interaction among the components of DSB end repair machinery. Our results also show that ScMre11 by itself binds to DSB ends, then promotes end bridging of duplex DNA, and directly interacts with Sae2. We discuss the implications of these results in the context of an alternative mechanism for DSB end processing and the generation of single-stranded DNA for DNA repair and homologous recombination.

Estimation of Probabilistic Bounds on Phase CPI and Relevance in WCET Analysis

Estimating program worst case execution time(WCET) accurately and efficiently is a challenging task. Several programs exhibit phase behavior wherein cycles per instruction (CPI) varies in phases during execution. Recent work has suggested the use of phases in such programs to estimate WCET with minimal instrumentation. However the suggested model uses a function of mean CPI that has no probabilistic guarantees. We propose to use Chebyshev's inequality that can be applied to any arbitrary distribution of CPI samples, to probabilistically bound CPI of a phase. Applying Chebyshev's inequality to phases that exhibit high CPI variation leads to pessimistic upper bounds. We propose a mechanism that refines such phases into sub-phases based on program counter(PC) signatures collected using profiling and also allows the user to control variance of CPI within a sub-phase. We describe a WCET analyzer built on these lines and evaluate it with standard WCET and embedded benchmark suites on two different architectures for three chosen probabilities, p={0.9, 0.95 and 0.99}. For p= 0.99, refinement based on PC signatures alone, reduces average pessimism of WCET estimate by 36%(77%) on Arch1 (Arch2). Compared to Chronos, an open source static WCET analyzer, the average improvement in estimates obtained by refinement is 5%(125%) on Arch1 (Arch2). On limiting variance of CPI within a sub-phase to {50%, 10%, 5% and 1%} of its original value, average accuracy of WCET estimate improves further to {9%, 11%, 12% and 13%} respectively, on Arch1. On Arch2, average accuracy of WCET improves to 159% when CPI variance is limited to 50% of its original value and improvement is marginal beyond that point.

Fast and efficient automatic memory management for GPUs using compiler-assisted runtime coherence scheme

Exploiting the performance potential of GPUs requires managing the data transfers to and from them efficiently which is an error-prone and tedious task. In this paper, we develop a software coherence mechanism to fully automate all data transfers between the CPU and GPU without any assistance from the programmer. Our mechanism uses compiler analysis to identify potential stale accesses and uses a runtime to initiate transfers as necessary. This allows us to avoid redundant transfers that are exhibited by all other existing automatic memory management proposals. We integrate our automatic memory manager into the X10 compiler and runtime, and find that it not only results in smaller and simpler programs, but also eliminates redundant memory transfers. Tested on eight programs ported from the Rodinia benchmark suite it achieves (i) a 1.06x speedup over hand-tuned manual memory management, and (ii) a 1.29x speedup over another recently proposed compiler--runtime automatic memory management system. Compared to other existing runtime-only and compiler-only proposals, it also transfers 2.2x to 13.3x less data on average.

Multiple sub-row buffers in DRAM: unlocking performance and energy improvement opportunities

The twin demands of energy-efficiency and higher performance on DRAM are highly emphasized in multicore architectures. A variety of schemes have been proposed to address either the latency or the energy consumption of DRAMs. These schemes typically require non-trivial hardware changes and end up improving latency at the cost of energy or vice-versa. One specific DRAM performance problem in multicores is that interleaved accesses from different cores can potentially degrade row-buffer locality. In this paper, based on the temporal and spatial locality characteristics of memory accesses, we propose a reorganization of the existing single large row-buffer in a DRAM bank into multiple sub-row buffers (MSRB). This re-organization not only improves row hit rates, and hence the average memory latency, but also brings down the energy consumed by the DRAM. The first major contribution of this work is proposing such a reorganization without requiring any significant changes to the existing widely accepted DRAM specifications. Our proposed reorganization improves weighted speedup by 35.8%, 14.5% and 21.6% in quad, eight and sixteen core workloads along with a 42%, 28% and 31% reduction in DRAM energy. The proposed MSRB organization enables opportunities for the management of multiple row-buffers at the memory controller level. As the memory controller is aware of the behaviour of individual cores it allows us to implement coordinated buffer allocation schemes for different cores that take into account program behaviour. We demonstrate two such schemes, namely Fairness Oriented Allocation and Performance Oriented Allocation, which show the flexibility that memory controllers can now exploit in our MSRB organization to improve overall performance and/or fairness. Further, the MSRB organization enables additional opportunities for DRAM intra-bank parallelism and selective early precharging of the LRU row-buffer to further improve memory access latencies. These two optimizations together provide an additional 5.9% performance improvement.

Endoplasmic Reticulum Stress-Mediated Activation of p38 MAPK, Caspase-2 and Caspase-8 Leads to Abrin-Induced Apoptosis

Abrin from Abrus precatorius plant is a potent protein synthesis inhibitor and induces apoptosis in cells. However, the relationship between inhibition of protein synthesis and apoptosis is not well understood. Inhibition of protein synthesis by abrin can lead to accumulation of unfolded protein in the endoplasmic reticulum causing ER stress. The observation of phosphorylation of eukaryotic initiation factor 2 alpha and upregulation of CHOP (CAAT/enhancer binding protein (C/EBP) homologous protein), important players involved in ER stress signaling by abrin, suggested activation of ER stress in the cells. ER stress is also known to induce apoptosis via stress kinases such as p38 MAPK and JNK. Activation of both the pathways was observed upon abrin treatment and found to be upstream of the activation of caspases. Moreover, abrin-induced apoptosis was found to be dependent on p38 MAPK but not JNK. We also observed that abrin induced the activation of caspase-2 and caspase-8 and triggered Bid cleavage leading to mitochondrial membrane potential loss and thus connecting the signaling events from ER stress to mitochondrial death machinery.

Automatic Data Allocation and Buffer Management for Multi-GPU Machines

Multi-GPU machines are being increasingly used in high-performance computing. Each GPU in such a machine has its own memory and does not share the address space either with the host CPU or other GPUs. Hence, applications utilizing multiple GPUs have to manually allocate and manage data on each GPU. Existing works that propose to automate data allocations for GPUs have limitations and inefficiencies in terms of allocation sizes, exploiting reuse, transfer costs, and scalability. We propose a scalable and fully automatic data allocation and buffer management scheme for affine loop nests on multi-GPU machines. We call it the Bounding-Box-based Memory Manager (BBMM). BBMM can perform at runtime, during standard set operations like union, intersection, and difference, finding subset and superset relations on hyperrectangular regions of array data (bounding boxes). It uses these operations along with some compiler assistance to identify, allocate, and manage data required by applications in terms of disjoint bounding boxes. This allows it to (1) allocate exactly or nearly as much data as is required by computations running on each GPU, (2) efficiently track buffer allocations and hence maximize data reuse across tiles and minimize data transfer overhead, and (3) and as a result, maximize utilization of the combined memory on multi-GPU machines. BBMM can work with any choice of parallelizing transformations, computation placement, and scheduling schemes, whether static or dynamic. Experiments run on a four-GPU machine with various scientific programs showed that BBMM reduces data allocations on each GPU by up to 75% compared to current allocation schemes, yields performance of at least 88% of manually written code, and allows excellent weak scaling.

Biomechanics of substrate boring by fig wasps

Female insects of diverse orders bore into substrates to deposit their eggs. Such insects must overcome several biomechanical challenges to successfully oviposit, which include the selection of suitable substrates through which the ovipositor can penetrate without itself fracturing. In many cases, the insect may also need to steer and manipulate the ovipositor within the substrate to deliver eggs at desired locations before rapidly retracting her ovipositor to avoid predation. In the case of female parasitoid ichneumonid wasps, this process is repeated multiple times during her lifetime, thus testing the ability of the ovipositioning apparatus to endure fracture and fatigue. What specific adaptations does the ovipositioning apparatus of a female ichneumonoid wasp possess to withstand these challenges? We addressed this question using a model system composed of parasitoid and pollinator fig wasps. First, we show that parasitoid ovipositor tips have teeth-like structures, preferentially enriched with zinc, unlike the smooth morphology of pollinator ovipositors. We describe sensillae present on the parasitoid ovipositor tip that are likely to aid in the detection of chemical species and mechanical deformations and sample microenvironments within the substrate. Second, using atomic force microscopy, we show that parasitoid tip regions have a higher modulus compared with regions proximal to the abdomen in parasitoid and pollinator ovipositors. Finally, we use videography to film wasps during substrate boring and analyse buckling of the ovipositor to estimate the forces required for substrate boring. Together, these results allow us to describe the biomechanical principles underlying substrate boring in parasitoid ichneumonid wasps. Such studies may be useful for the biomimetic design of surgical tools and in the use of novel mechanisms to bore through hard substrates.