Flexible Filters: Load Balancing through Backpressure for Stream Programs

Stream processing is a promising paradigm for programming multi-core systems for high-performance embedded applications. We propose flexible filters as a technique that combines static mapping of the stream program tasks with dynamic load balancing of their execution. The goal is to improve the system-level processing throughput of the program when it is executed on a distributed-memory multi-core system as well as the local (core-level) memory utilization. Our technique is distributed and scalable because it is based on point-to-point handshake signals exchanged between neighboring cores. Load balancing with flexible filters can be applied to stream applications that present large dynamic variations in the computational load of their tasks and the dimension of the stream data tokens. In order to demonstrate the practicality of our technique, we present the performance improvements for the case study of a JPEG encoder running on the IBM Cell multi-core processor

Topology-Based Performance Analysis and Optimization of Latency-Insensitive Systems

Latency-insensitive protocols allow system-on-chip engineers to decouple the design of the computing cores from the design of the inter-core communication channels while following the synchronous design paradigm. In a latency-insensitive system (LIS) each core is encapsulated within a shell, a synthesized interface module that dynamically controls its operation. At each clock period, if new data has not arrived on an input channel or a stalling request has arrived on an output channel, the shell stalls the core and buffers other incoming valid data for future processing. The combination of finite buffers and backpressure from stalling can cause throughput degradation. Previous works addressed this problem by increasing buffer space to reduce the backpressure requests or inserting extra buffering to balance the channel latency around a LIS. We explore the theoretical complexity of these approaches and propose a heuristic algorithm for efficient queue sizing. We also practically characterize several LIS topologies and how the topology of a LIS can impact not only how much throughput degradation will occur, but also the difficulty of finding optimal queue sizing solutions

A Recursive Data-Driven Approach to Programming Multicore Systems

In this paper, we propose a method to program divide-and-conquer problems on multicore systems that is based on a data-driven recursive programming model. Data intensive programs are difficult to program on multicore architectures because they require efficient utilization of inter-core communication. Models for programming multicore systems available today generally lack the ability to automatically extract concurrency from a sequential style program and map concurrent tasks to efficiently leverage data and temporal locality. For divide-and-conquer algorithms, a recursive programming model can address both of these problems. Furthermore, since a recursive function has the same behavior patterns at all granularities of a problem, the same recursive model can be used to implement a multicore program at all of its levels: 1. the operations of a single core, 2. how to distribute tasks among several cores, and 3. in what order to schedule tasks on a multicore system when it is not possible to schedule all of the tasks at the same time. We present a novel selective execution technique that can enable automatic parallelization and task mapping of a recursive program onto a multicore system. To verify the practicality of this approach, we perform a case-study of bitonic sort on the Cell BE processor

Are our actions aligned with our evidence? The skinny on changing the landscape of obesity.

Recent debate about the role of food deserts in the United States (i.e., places that lack access to healthy foods) has prompted discussion on policies being enacted, including efforts that encourage the placement of full-service supermarkets into food deserts. Other initiatives to address obesogenic neighborhood features include land use zoning and parks renovations. Yet, there is little evidence to demonstrate that such policies effect change. While we suspect most researchers and policymakers would agree that effective neighborhood change could be a powerful tool in combating obesity, we desperately need strong and sound evidence to guide decisions about where and how to invest

FACTORS INFLUENCING WEST TENNESSEE FARMERS' WILLINGNESS TO PAY FOR A BOLL WEEVIL ERADICATION PROGRAM

Data from a survey were used to evaluate Tennessee farmers' willingness to pay for the boll weevil eradication program. Producer experience, boll weevil control costs, and attitudes about boll weevil damage and insecticide usage after the program were significant explanatory variables and had a positive influence on willingness to pay.Contingent valuation, cotton, regional pest control, pest management groups, Demand and Price Analysis, Resource /Energy Economics and Policy,

Data-Driven Programming Abstractions and Optimization for Multi-Core Platforms

Multi-core platforms have spread to all corners of the computing industry, and trends in design and power indicate that the shift to multi-core will become even wider-spread in the future. As the number of cores on a chip rises, the complexity of memory systems and on-chip interconnects increases drastically. The programmer inherits this complexity in the form of new responsibilities for task decomposition, synchronization, and data movement within an application, which hitherto have been concealed by complex processing pipelines or deemed unimportant since tasks were largely executed sequentially. To some extent, the need for explicit parallel programming is inevitable, due to limits in the instruction-level parallelism that can be automatically extracted from a program. However, these challenges create a great opportunity for the development of new programming abstractions which hide the low-level architectural complexity while exposing intuitive high-level mechanisms for expressing parallelism. Many models of parallel programming fall into the category of data-centric models, where the structure of an application depends on the role of data and communication in the relationships between tasks. The utilization of the inter-core communication networks and effective scaling to large data sets are decidedly important in designing efficient implementations of parallel applications. The questions of how many low-level architectural details should be exposed to the programmer, and how much parallelism in an application a programmer should expose to the compiler remain open-ended, with different answers depending on the architecture and the application in question. I propose that the key to unlocking the capabilities of multi-core platforms is the development of abstractions and optimizations which match the patterns of data movement in applications with the inter-core communication capabilities of the platforms. After a comparative analysis that confirms and stresses the importance of finding a good match between the programming abstraction, the application, and the architecture, this dissertation proposes two techniques that showcase the power of leveraging data dependency patterns in parallel performance optimizations. Flexible Filters dynamically balance load in stream programs by creating flexibility in the runtime data flow through the addition of redundant stream filters. This technique combines a static mapping with dynamic flow control to achieve light-weight, distributed and scalable throughput optimization. The properties of stream communication, i.e., FIFO pipes, enable flexible filters by exposing the backpressure dependencies between tasks. Next, I present Huckleberry, a novel recursive programming abstraction developed in order to allow programmers to expose data locality in divide-and-conquer algorithms at a high level of abstraction. Huckleberry automatically converts sequential recursive functions with explicit data partitioning into parallel implementations that can be ported across changes in the underlying architecture including the number of cores and the amount of on-chip memory. I then present a performance model for multi-core applications which provides an efficient means to evaluate the trade-offs between the computational and communication requirements of applications together with the hardware resources of a target multi-core architecture. The model encompasses all data-driven abstractions that can be reduced to a task graph representation and is extensible to performance techniques such as Flexible Filters that alter an application's original task graph. Flexible Filters and Huckleberry address the challenges of parallel programming on multi-core architectures by taking advantage of properties specific to the stream and recursive paradigms, and the performance model creates a unifying framework based on the communication between tasks in parallel applications. Combined, these contributions demonstrate that specialization with respect to communication patterns enhances the ability of parallel programming abstractions and optimizations to harvest the power of multi-core platforms

Split graphs and Block Representations

In this paper, we study split graphs and related classes of graphs from the perspective of their sequence of vertex degrees and an associated lattice under majorization. Following the work of Merris in 2003, we define blocks $[\alpha(\pi)|\beta(\pi)]$, where $\pi$ is the degree sequence of a graph, and $\alpha(\pi)$ and $\beta(\pi)$ are sequences arising from $\pi$. We use the block representation $[\alpha(\pi)|\beta(\pi)]$ to characterize membership in each of the following classes: unbalanced split graphs, balanced split graphs, pseudo-split graphs, and three kinds of Nordhaus-Gaddum graphs (defined by Collins and Trenk in 2013). As in Merris' work, we form a poset under the relation majorization in which the elements are the blocks $[\alpha(\pi)|\beta(\pi)]$ representing split graphs with a fixed number of edges. We partition this poset in several interesting ways using what we call amphoras, and prove upward and downward closure results for blocks arising from different families of graphs. Finally, we show that the poset becomes a lattice when a maximum and minimum element are added, and we prove properties of the meet and join of two blocks.Comment: 23 pages, 7 Figures, 2 Table

Impact of consensus guidelines for breast-conserving surgery in patients with ductal carcinoma in situ

BACKGROUND: Consensus guidelines published in 2016 recommended a 2 mm free margin as the standard for negative margins in patients undergoing breast-conserving surgery (BCS) for ductal carcinoma in situ (DCIS). The goal of the guideline recommendation was standardization of re-excision practices. AIMS: To evaluate the impact of this consensus guideline on our institutional practices. METHODS: We identified all patients at our institution with pure DCIS who were initially treated with BCS from September 2014 to August 2018 using a prospectively-maintained institutional database. A retrospective chart review was performed to determine margin status and re-excision rates during the 2 years before and the 2 years after the guideline was published in order to determine the effect on our re-excision rates. Close margins were defined as \u3c2 mm. RESULTS: In the 2 years before the consensus guideline was published, 184 patients with DCIS underwent BCS. Twenty-six patients had positive margins and 24 underwent re-excision, including three who had completion mastectomy. Of the remaining 159 patients, 76 had ≥2 mm (negative) margins. The remaining 82 patients had close margins and 48 of these patients (58.5%) underwent re-excision, including one who had a completion mastectomy. Excluding the patients with positive margins, our re-excision rate was 30.4% prior to the guideline. In the 2 years after the consensus guideline was published, 192 patients with DCIS underwent initial BCS. Twenty-four patients had positive margins and 22 underwent re-excision, including three who had completion mastectomy. Of the remaining 168 patients, 95 patients had ≥2 mm (negative) margins. The remaining 73 patients had close margins and 45 of those patients (61.6%) underwent re-excision, including six who had completion mastectomy. Excluding the patients with positive margins, our re-excision rate was 26.8% after the guideline. CONCLUSIONS: Our institution\u27s re-excision rate did not change significantly during the 2 years before and after the publication of the consensus guideline on adequate margins for patients undergoing BCT for DCIS. Our overall re-excision rate decreased slightly. However, of the patients who had close margins, a larger proportion underwent re-excision after the guideline was published. The guideline publication appears to have affected our institutional practices slightly, but not dramatically as many of our surgeons\u27 practices were comparable to the guideline recommendations prior to 2016. We continue to use clinical judgment based on patient and tumor characteristics in deciding which patients will benefit from margin re-excision

Summary Report for the 2005-2006 STATEMAP Project: Geologic Mapping to Support Improved Database Development and Understanding of Urban Corridors, Critical Acquifers. And Special Areas of Environmental Concern in Texas

Eleven geologic maps, 1:24,000 scale, have been constructed for Galveston and Mustang Barrier Islands and for part of the Brazos River Valley and its aquifers. The maps are intended to be used by professionals and laypersons as a source of general geologic information that relates to land and resource use and management. The geologic maps of the barrier islands include (a) Northern Mustang Island (Port Aransas quadrangle), (b) Southern Mustang Island (Crane Islands NW quadrangle), (c) Northeastern Galveston Island (Galveston quadrangle), (d) Central Galveston Island (Lake Como quadrangle), and (e) Southeastern Galveston Island (Sea Isle and San Luis Pass quadrangles). These maps display island wetland and upland geologic environments. Geologic maps of the Brazos River Valley study area include six quadrangles: Baileyville, Hammond, Maysfield, Calvert, Gause, and Hearne South. These maps and cross sections show the geologic framework of the Brazos alluvial aquifer in an area where it intersects three other Texas aquifers: the Carrizo-Wilcox, Queen City, and Sparta.Bureau of Economic Geolog