Accurate modeling of core and memory locality for proxy generation targeting emerging applications and architectures

Designing optimal computer systems for improved performance and energy efficiency requires architects and designers to have a deep understanding of the end-user workloads. However, many end-users (e.g., large corporations, banks, defense organizations, etc.) are apprehensive to share their applications with designers due to the confidential nature of software code and data. In addition, emerging applications pose significant challenges to early design space exploration due to their long-running nature and the highly complex nature of their software stack that cannot be supported on many early performance models. The above challenges can be overcome by using a proxy benchmark. A miniaturized proxy benchmark can be used as a substitute of the original workload to perform early computer performance evaluation. The process of generating a proxy benchmark consists of extracting a set of key statistics to summarize the behavior of end-user applications through profiling and using the collected statistics to synthesize a representative proxy benchmark. Using such proxy benchmarks can help designers to understand the behavior of end-user’s workloads in a reasonable time without the users having to disclose sensitive information about their workloads. Prior proxy benchmarking schemes leverage micro-architecture independent metrics, derived from detailed simulation tools, to generate proxy benchmarks. However, many emerging workloads do not work reliably with many profiling or simulation tools, in which case it becomes impossible to apply prior proxy generation techniques to generate proxy benchmarks for such complex applications. Furthermore, these techniques model instruction pipeline-level locality in great detail, but abstract out memory locality modeling using simple stride-based models. This results in poor cloning accuracy especially for emerging applications, which have larger memory footprints and complex access patterns. A few detailed cache and memory locality modeling techniques have also been proposed in literature. However, these techniques either model limited locality metrics and suffer from poor cloning accuracy or are fairly accurate, but at the expense of significant metadata overhead. Finally, none of the prior proxy benchmarking techniques model both core and memory locality with high accuracy. As a result, they are not useful for studying system-level performance behavior. Keeping the above key limitations and shortcomings of prior work in mind, this dissertation presents several techniques that expand the frontiers of workload proxy benchmarking, thereby enabling computer designers to gain a better and faster understanding of end-user application behavior without compromising the privileged nature of software or data. This dissertation first presents a core-level proxy benchmark generation methodology that leverages performance metrics derived from hardware performance counter measurements to create miniature proxy benchmarks targeting emerging big-data applications. The presented performance counter based characterization and associated extrapolation into generic parameters for proxy generation enables faster analysis (runs almost at native hardware speeds, unlike prior workload cloning proposals) and proxy generation for emerging applications that do not work with simulators or profiling tools. The generated proxy benchmarks are representative of the performance of the real-world big-data applications, including operating system and run-time effects, and yet converge to results quickly without needing any complex software stack support. Next, to improve upon the accuracy and efficiency of prior memory proxy benchmarking techniques, this dissertation presents a novel memory locality modeling technique that leverages localized pattern detection to create miniature memory proxy benchmarks. The presented technique models memory reference locality by decomposing an application’s memory accesses into a set of independent streams (localized by using address region based localization property), tracking fine-grained patterns within the localized streams and, finally, chaining or interleaving accesses from different localized memory streams to create an ordered proxy memory access sequence. This dissertation further extends the workload cloning approach to Graphics Processing Units (GPUs) and presents a novel proxy generation methodology to model the inherent memory access locality of GPU applications, while also accounting for the GPU’s parallel execution model. The generated memory proxy benchmarks help to enable fast and efficient design space exploration of futuristic memory hierarchies. Finally, this dissertation presents a novel technique to integrate accurate core and memory locality models to create system-level proxy benchmarks targeting emerging applications. This is a new capability that can facilitate efficient overall system (core, cache and memory subsystem) design-space exploration. This dissertation further presents a novel methodology that exploits the synthetic benchmark generation framework to create hypothetical workloads with performance behavior that does not currently exist. Such proxies can be generated to cover anticipated code trends and can represent futuristic workloads before the workloads even exist.Electrical and Computer Engineerin

7th Annual Jackson School of Geosciences Student Research Symposium, February 3, 2018

ConocoPhillipsGeological Science

Holdsworth Retrofit and Renovation

The University of Massachusetts has a rapidly evolving commitment to reducing greenhouse gas emissions and improving the environmental sustainability of its operations. According to the most recent IPCC report, the buildings sector has more potential to contribute to climate change mitigation than any other sector.1 The energy efficient designs of the current spate of building projects are indicative of the University’s commitment to green building—reducing the energy intensity of the university relative to building area and activities. However, these efforts cannot reduce the total energy use or greenhouse gas emissions from current levels. Among the University’s assets with the greatest potential to achieve these goals are its existing buildings. Most of these are good buildings that have not reached the end of their useful life. Forty-two buildings, encompassing more than half of the general administration and educational space fall into the categories of “catch up and keep up” or “keep and renew” according to the university’s Building Disposition Report.2 Many of the existing buildings have great historical, aesthetic, and emotional value and have stood the test of time as the site of the academic, scientific, and cultural work that is their primary purpose. Can these buildings be updated to dramatically reduce their energy consumption and allow them to continue to function as valuable assets for the long term? What levels of energy savings are possible and reasonable? This report is designed to answer these questions for one representative building: Holdsworth Hall. The recommendations in this report are the product of a detailed and careful examination and exploration of the building and its operations. The investigations and proposed solutions are motivated by two principles: First, the architectural intention should be respected. The building as designed works well on many levels, and no recommendation should undermine currently effective systems and designs or compromise the aesthetic intention of its designers. Second, the building is a complex system, and no change can be considered in isolation. Single measures may achieve savings, but cannot maximize savings or performance without complementary changes in related systems. A final package of recommended measures will define a new building system with emergent properties that make for a qualitatively different and better building beyond simple energy consumption metrics. 1

Fabricate 2020

Fabricate 2020 is the fourth title in the FABRICATE series on the theme of digital fabrication and published in conjunction with a triennial conference (London, April 2020). The book features cutting-edge built projects and work-in-progress from both academia and practice. It brings together pioneers in design and making from across the fields of architecture, construction, engineering, manufacturing, materials technology and computation. Fabricate 2020 includes 32 illustrated articles punctuated by four conversations between world-leading experts from design to engineering, discussing themes such as drawing-to-production, behavioural composites, robotic assembly, and digital craft

Empirical Modeling and Its Applications

Empirical modeling has been a useful approach for the analysis of different problems across numerous areas/fields of knowledge. As it is known, this type of modeling is particularly helpful when parametric models, due to various reasons, cannot be constructed. Based on different methodologies and approaches, empirical modeling allows the analyst to obtain an initial understanding of the relationships that exist among the different variables that belong to a particular system or process. In some cases, the results from empirical models can be used in order to make decisions about those variables, with the intent of resolving a given problem in the real-life applications. This book entitled Empirical Modeling and Its Applications consists of six (6) chapters

Geologic processes that control sourcing and migration of subsurface helium

There is an ever-pressing need to find more helium (He) because 1) it is an essential resource for modern life, 2) reserves are dwindling faster than He accumulations are discovered, and 3) new He projects are delayed. The motivation for this work is to provide updated frameworks on the geologic processes and migration mechanisms of He in the mid-continent USA, using noble gas geochemistry, structural geology and geophysics. The Colorado Plateau field area (Four Corners area), USA was chosen to represent a moderate tectonic activity environment, and Yellowstone (and its environs), USA, were chosen to represent a very tectonically active region and to investigate the impact of heat on gas release. In the Four Corners area, utilizing bulk gas and isotopes of hydrocarbons, non-hydrocarbons, and noble gases (n=31), we construct mass balance and noble gas fractionation models that provide evidence for advective fault-controlled systems responsible for basement sourced He accumulations. Regarding Yellowstone, utilizing heat flow data, bulk gas, and isotopes of non-hydrocarbons and noble gases (n=43), we quantify gas origin, fluid flow, and heat influence in a regional context using noble gas heat and fractionation models. We show a poor relationship regarding He and heat flow on a regional scale for Yellowstone, and we propose that localized heat sources are important in releasing He trapped in minerals. Our prediction of fault-controlled He-systems in the Four Corners area is corroborated with high-resolution geophysical data that shows a strong non-random relationship with He-rich occurrences and structural features (faults/intrusions) and historical He-well data (n=94). Based on the distributions of these relationships, we create a regional probabilistic predictive He map to reduce exploration risk. Additional work utilizing soil gas data (n=1974), was used to construct a higher-resolution localized predictive model calibrated with real-world data illustrating areas that are higher-likelihood of containing He-rich gas