Uintah and Related C-SAFE Publications

2015


A. Humphrey, T. Harman, M. Berzins, P. Smith. “A Scalable Algorithm for Radiative Heat Transfer Using Reverse Monte Carlo Ray Tracing,” In High Performance Computing, Lecture Notes in Computer Science, Vol. 9137, Edited by Kunkel, Julian M. and Ludwig, Thomas, Springer International Publishing, pp. 212-230. 2015.
ISBN: 978-3-319-20118-4
DOI: 10.1007/978-3-319-20119-1_16

ABSTRACT

Radiative heat transfer is an important mechanism in a class of challenging engineering and research problems. A direct all-to-all treatment of these problems is prohibitively expensive on large core counts due to pervasive all-to-all MPI communication. The massive heat transfer problem arising from the next generation of clean coal boilers being modeled by the Uintah framework has radiation as a dominant heat transfer mode. Reverse Monte Carlo ray tracing (RMCRT) can be used to solve for the radiative-flux divergence while accounting for the effects of participating media. The ray tracing approach used here replicates the geometry of the boiler on a multi-core node and then uses an all-to-all communication phase to distribute the results globally. The cost of this all-to-all is reduced by using an adaptive mesh approach in which a fine mesh is only used locally, and a coarse mesh is used elsewhere. A model for communication and computation complexity is used to predict performance of this new method. We show this model is consistent with observed results and demonstrate excellent strong scaling to 262K cores on the DOE Titan system on problem sizes that were previously computationally intractable.

Keywords: Uintah; Radiation modeling; Parallel; Scalability; Adaptive mesh refinement; Simulation science; Titan



J.A. Nairn, J.E. Guilkey. “Axisymmetric Form of the Generalized Interpolation Material Point Method,” In Int. J. for Numerical Methods in Engineering, Vol. 101, pp. 127-147. 2015.
DOI: 10.1002/nme.4792

ABSTRACT

This paper reformulates the axisymmetric form of the material point method (MPM) using generalized interpolation material point (GIMP) methods. The reformulation led to a need for new shape functions and gradients specific for axisymmetry that were not available before. The new shape functions differ most from planar shape functions near the origin where r=0. A second purpose for this paper was to evaluate the consequences of axisymmetry on a variety MPM extensions that have been developed since the original work on axisymmetric MPM. These extensions included convected particle domain integration (CPDI), traction boundary conditions, explicit cracks, multimaterial mode MPM for contact, thermal conduction, and solvent diffusion. Some examples show that the axisymmetric shape functions work well and are especially crucial near the origin. One real-world example is given for modeling a cylinder-penetration problem. Finally, a check list for software development describes all tasks needed to convert 2D planar or 3D codes to include an option for axisymmetric MPM.



B. Peterson, N. Xiao, J. Holmen, S. Chaganti, A. Pakki, J. Schmidt, D. Sunderland, A. Humphrey, M. Berzins. “Developing Uintah’s Runtime System For Forthcoming Architectures,” Subtitled “Refereed paper presented at the RESPA 15 Workshop at SuperComputing 2015 Austin Texas,” SCI Institute, 2015.



B. Peterson, H. K. Dasari, A. Humphrey, J.C. Sutherland, T. Saad, M. Berzins. “Reducing overhead in the Uintah framework to support short-lived tasks on GPU-heterogeneous architectures,” In Proceedings of the 5th International Workshop on Domain-Specific Languages and High-Level Frameworks for High Performance Computing (WOLFHPC'15), ACM, pp. 4:1-4:8. 2015.
DOI: 10.1145/2830018.2830023


2014


A. Dubey, A. Almgren, John Bell, M. Berzins, S. Brandt, G. Bryan, P. Colella, D. Graves, M. Lijewski, F. Löffler, B. O’Shea, E. Schnetter, B. Van Straalen, K. Weide. “A survey of high level frameworks in block-structured adaptive mesh refinement packages,” In Journal of Parallel and Distributed Computing, 2014.
DOI: 10.1016/j.jpdc.2014.07.001

ABSTRACT

Over the last decade block-structured adaptive mesh refinement (SAMR) has found increasing use in large, publicly available codes and frameworks. SAMR frameworks have evolved along different paths. Some have stayed focused on specific domain areas, others have pursued a more general functionality, providing the building blocks for a larger variety of applications. In this survey paper we examine a representative set of SAMR packages and SAMR-based codes that have been in existence for half a decade or more, have a reasonably sized and active user base outside of their home institutions, and are publicly available. The set consists of a mix of SAMR packages and application codes that cover a broad range of scientific domains. We look at their high-level frameworks, their design trade-offs and their approach to dealing with the advent of radical changes in hardware architecture. The codes included in this survey are BoxLib, Cactus, Chombo, Enzo, FLASH, and Uintah.

Keywords: SAMR, BoxLib, Chombo, FLASH, Cactus, Enzo, Uintah



A. Faucett, T. Harman, T. Ameel. “Computational Determination of the Modified Vortex Shedding Frequency for a Rigid, Truncated, Wall-Mounted Cylinder in Cross Flow,” In Volume 10: Micro- and Nano-Systems Engineering and Packaging, Montreal, ASME International Mechanical Engineering Congress and Exposition (IMECE), International Conference on Computational Science, November, 2014.
DOI: 10.1115/imece2014-39064



A. Humphrey, Q. Meng, M. Berzins, D. Caminha B.de Oliveira, Z. Rakamaric, G. Gopalakrishnan. “Systematic Debugging Methods for Large-Scale HPC Computational Frameworks,” In Computing in Science Engineering, Vol. 16, No. 3, pp. 48--56. May, 2014.
ISSN: 1521-9615
DOI: 10.1109/MCSE.2014.11

ABSTRACT

Parallel computational frameworks for high performance computing (HPC) are central to the advancement of simulation based studies in science and engineering. Unfortunately, finding and fixing bugs in these frameworks can be extremely time consuming. Left unchecked, these bugs can drastically diminish the amount of new science that can be performed. This paper presents our systematic study of the Uintah Computational Framework, and our approaches to debug it more incisively. Our key insight is to leverage the modular structure of Uintah which lends itself to systematic debugging. In particular, we have developed a new approach based on Coalesced Stack Trace Graphs (CSTGs) that summarize the system behavior in terms of key control flows manifested through function invocation chains. We illustrate several scenarios how CSTGs could help efficiently localize bugs, and present a case study of how we found and fixed a real Uintah bug using CSTGs.

Keywords: Computational Modeling and Frameworks, Parallel Programming, Reliability, Debugging Aids



Q. Meng, M. Berzins. “Scalable large-scale fluid-structure interaction solvers in the Uintah framework via hybrid task-based parallelism algorithms,” In Concurrency and Computation: Practice and Experience, Vol. 26, No. 7, pp. 1388--1407. May, 2014.
DOI: 10.1002/cpe

ABSTRACT

Uintah is a software framework that provides an environment for solving fluid–structure interaction problems on structured adaptive grids for large-scale science and engineering problems involving the solution of partial differential equations. Uintah uses a combination of fluid flow solvers and particle-based methods for solids, together with adaptive meshing and a novel asynchronous task-based approach with fully automated load balancing. When applying Uintah to fluid–structure interaction problems, the combination of adaptive mesh- ing and the movement of structures through space present a formidable challenge in terms of achieving scalability on large-scale parallel computers. The Uintah approach to the growth of the number of core counts per socket together with the prospect of less memory per core is to adopt a model that uses MPI to communicate between nodes and a shared memory model on-node so as to achieve scalability on large-scale systems. For this approach to be successful, it is necessary to design data structures that large numbers of cores can simultaneously access without contention. This scalability challenge is addressed here for Uintah, by the development of new hybrid runtime and scheduling algorithms combined with novel lock-free data structures, making it possible for Uintah to achieve excellent scalability for a challenging fluid–structure problem with mesh refinement on as many as 260K cores.

Keywords: MPI, threads, Uintah, many core, lock free, fluid-structure interaction, c-safe



Qingyu Meng. “Large-Scale Distributed Runtime System for DAG-Based Computational Framework,” Note: Ph.D. in Computer Science, advisor Martin Berzins, School of Computing, University of Utah, August, 2014.

ABSTRACT

Recent trends in high performance computing present larger and more diverse computers using multicore nodes possibly with accelerators and/or coprocessors and reduced memory. These changes pose formidable challenges for applications code to attain scalability. Software frameworks that execute machine-independent applications code using a runtime system that shields users from architectural complexities offer a portable solution for easy programming. The Uintah framework, for example, solves a broad class of large-scale problems on structured adaptive grids using fluid-flow solvers coupled with particle-based solids methods. However, the original Uintah code had limited scalability as tasks were run in a predefined order based solely on static analysis of the task graph and used only message passing interface (MPI) for parallelism. By using a new hybrid multithread and MPI runtime system, this research has made it possible for Uintah to scale to 700K central processing unit (CPU) cores when solving challenging fluid-structure interaction problems. Those problems often involve moving objects with adaptive mesh refinement and thus with highly variable and unpredictable work patterns. This research has also demonstrated an ability to run capability jobs on the heterogeneous systems with Nvidia graphics processing unit (GPU) accelerators or Intel Xeon Phi coprocessors. The new runtime system for Uintah executes directed acyclic graphs of computational tasks with a scalable asynchronous and dynamic runtime system for multicore CPUs and/or accelerators/coprocessors on a node. Uintah's clear separation between application and runtime code has led to scalability increases without significant changes to application code. This research concludes that the adaptive directed acyclic graph (DAG)-based approach provides a very powerful abstraction for solving challenging multiscale multiphysics engineering problems. Excellent scalability with regard to the different processors and communications performance are achieved on some of the largest and most powerful computers available today.



D.C.B. de Oliveira, A. Humphrey, Q. Meng, Z. Rakamaric, M. Berzins, G. Gopalakrishnan. “Systematic Debugging of Concurrent Systems Using Coalesced Stack Trace Graphs,” In Proceedings of the 27th International Workshop on Languages and Compilers for Parallel Computing (LCPC), September, 2014.

ABSTRACT

A central need during software development of large-scale parallel systems is tools that help help to identify the root causes of bugs quickly. Given the massive scale of these systems, tools that highlight changes--say introduced across software versions or their operating conditions (e.g., inputs, schedules)--can prove to be highly effective in practice. Conventional debuggers, while good at presenting details at the problem-site (e.g., crash), often omit contextual information to identify the root causes of the bug. We present a new approach to collect and coalesce stack traces, leading to an efficient summary display of salient system control flow differences in a graphical form called Coalesced Stack Trace Graphs (CSTG). CSTGs have helped us understand and debug situations within a computational framework called Uintah that has been deployed at large scale, and undergoes frequent version updates. In this paper, we detail CSTGs through case studies in the context of Uintah where unexpected behaviors caused by different vesions of software or occurring across different time-steps of a system (e.g., due to non-determinism) are debugged. We show that CSTG also gives conventional debuggers a far more productive and guided role to play.



R. Stoll, E. Pardyjak, J.J. Kim, T. Harman, A.N. Hayati. “An inter-model comparison of three computation fluid dynamics techniques for step-up and step-down street canyon flows,” In ASME FEDSM/ICNMM symposium on urban fluid mechanics, August, 2014.


2013


J. Beckvermit, J. Peterson, T. Harman, S. Bardenhagen, C. Wight, Q. Meng, M. Berzins. “Multiscale Modeling of Accidental Explosions and Detonations,” In Computing in Science and Engineering, Vol. 15, No. 4, pp. 76--86. 2013.
DOI: 10.1109/MCSE.2013.89

ABSTRACT

Accidental explosions are exceptionally dangerous and costly, both in lives and money. Regarding world-wide conflict with small arms and light weapons, the Small Arms Survey has recorded over 297 accidental explosions in munitions depots across the world that have resulted in thousands of deaths and billions of dollars in damage in the past decade alone [45]. As the recent fertilizer plant explosion that killed 15 people in West, Texas demonstrates, accidental explosions are not limited to military operations. Transportation accidents also pose risks, as illustrated by the occasional train derailment/explosion in the nightly news, or the semi-truck explosion detailed in the following section. Unlike other industrial accident scenarios, explosions can easily affect the general public, a dramatic example being the PEPCON disaster in 1988, where windows were shattered, doors blown off their hinges, and flying glass and debris caused injuries up to 10 miles away.

While the relative rarity of accidental explosions speaks well of our understanding to date, their violence rightly gives us pause. A better understanding of these materials is clearly still needed, but a significant barrier is the complexity of these materials and the various length scales involved. In typical military applications, explosives are known to be ignited by the coalescence of hot spots which occur on micrometer scales. Whether this reaction remains a deflagration (burning) or builds to a detonation depends both on the stimulus and the boundary conditions or level of confinement. Boundary conditions are typically on the scale of engineered parts, approximately meters. Additional dangers are present at the scale of trucks and factories. The interaction of various entities, such as barrels of fertilizer or crates of detonators, admits the possibility of a sympathetic detonation, i.e. the unintended detonation of one entity by the explosion of another, generally caused by an explosive shock wave or blast fragments.

While experimental work has been and will continue to be critical to developing our fundamental understanding of explosive initiation, de agration and detonation, there is no practical way to comprehensively assess safety on the scale of trucks and factories experimentally. The scenarios are too diverse and the costs too great. Numerical simulation provides a complementary tool that, with the steadily increasing computational power of the past decades, makes simulations at this scale begin to look plausible. Simulations at both the micrometer scale, the "mesoscale", and at the scale of engineered parts, the "macro-scale", have been contributing increasingly to our understanding of these materials. Still, simulations on this scale require both massively parallel computational infrastructure and selective sampling of mesoscale response, i.e. advanced computational tools and modeling. The computational framework Uintah [1] has been developed for exactly this purpose.

Keywords: uintah, c-safe, accidents, explosions, military computing, risk analysis



M. Berzins, J. Schmidt, Q. Meng, A. Humphrey. “Past, Present, and Future Scalability of the Uintah Software,” In Proceedings of the Blue Waters Extreme Scaling Workshop 2012, pp. Article No.: 6. 2013.

ABSTRACT

The past, present and future scalability of the Uintah Software framework is considered with the intention of describing a successful approach to large scale parallelism and also considering how this approach may need to be extended for future architectures. Uintah allows the solution of large scale fluid-structure interaction problems through the use of fluid flow solvers coupled with particle-based solids methods. In addition Uintah uses a combustion solver to tackle a broad and challenging class of turbulent combustion problems. A unique feature of Uintah is that it uses an asynchronous task-based approach with automatic load balancing to solve complex problems using techniques such as adaptive mesh refinement. At present, Uintah is able to make full use of present-day massively parallel machines as the result of three phases of development over the past dozen years. These development phases have led to an adaptive scalable run-time system that is capable of independently scheduling tasks to multiple CPUs cores and GPUs on a node. In the case of solving incompressible low-mach number applications it is also necessary to use linear solvers and to consider the challenges of radiation problems. The approaches adopted to achieve present scalability are described and their extensions to possible future architectures is considered.

Keywords: netl, Uintah, parallelism, scalability, adaptive mesh refinement, linear equations



A. Biglari, T. Saad, J. Sutherland. “A Time-Accurate Pressure Projection Method for Reacting Flows,” In Proceedings of the SIAM 14th International Conference on Numerical Combustion (NC13), San Antonio, TX, 2013.



M. Hall, J.C. Beckvermit, C.A. Wight, T. Harman, M. Berzins. “The influence of an applied heat flux on the violence of reaction of an explosive device,” In Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery, San Diego, California, XSEDE '13, pp. 11:1--11:8. 2013.
ISBN: 978-1-4503-2170-9
DOI: 10.1145/2484762.2484786

ABSTRACT

It is well known that the violence of slow cook-off explosions can greatly exceed the comparatively mild case burst events typically observed for rapid heating. However, there have been few studies that examine the reaction violence as a function of applied heat flux that explore the dependence on heating geometry and device size. Here we report progress on a study using the Uintah Computation Framework, a high-performance computer model capable of modeling deflagration, material damage, deflagration to detonation transition and detonation for PBX9501 and similar explosives. Our results suggests the existence of a sharp threshold for increased reaction violence with decreasing heat flux. The critical heat flux was seen to increase with increasing device size and decrease with the heating of multiple surfaces, suggesting that the temperature gradient in the heated energetic material plays an important role the violence of reactions.

Keywords: DDT, cook-off, deflagration, detonation, violence of reaction, c-safe



Q. Meng, A. Humphrey, J. Schmidt, M. Berzins. “Preliminary Experiences with the Uintah Framework on Intel Xeon Phi and Stampede,” SCI Technical Report, No. UUSCI-2013-002, SCI Institute, University of Utah, 2013.

ABSTRACT

In this work, we describe our preliminary experiences on the Stampede system in the context of the Uintah Computational Framework. Uintah was developed to provide an environment for solving a broad class of fluid-structure interaction problems on structured adaptive grids. Uintah uses a combination of fluid-flow solvers and particle-based methods, together with a novel asynchronous taskbased approach and fully automated load balancing. While we have designed scalable Uintah runtime systems for large CPU core counts, the emergence of heterogeneous systems presents considerable challenges in terms of effectively utilizing additional on-node accelerators and co-processors, deep memory hierarchies, as well as managing multiple levels of parallelism. Our recent work has addressed the emergence of heterogeneous CPU/GPU systems with the design of a Unified heterogeneous runtime system, enabling Uintah to fully exploit these architectures with support for asynchronous, out-of-order scheduling of both CPU and GPU computational tasks. Using this design, Uintah has run at full scale on the Keeneland System and TitanDev. With the release of the Intel Xeon Phi co-processor and the recent availability of the Stampede system, we show that Uintah may be modified to utilize such a coprocessor based system. We also explore the different usage models provided by the Xeon Phi with the aim of understanding portability of a general purpose framework like Uintah to this architecture. These usage models range from the pragma based offload model to the more complex symmetric model, utilizing all co-processor and host CPU cores simultaneously. We provide preliminary results of the various usage models for a challenging adaptive mesh refinement problem, as well as a detailed account of our experience adapting Uintah to run on the Stampede system. Our conclusion is that while the Stampede system is easy to use, obtaining high performance from the Xeon Phi co-processors requires a substantial but different investment to that needed for GPU-based systems.

Keywords: Uintah, hybrid parallelism, scalability, parallel, adaptive, MIC, Xeon Phi, heterogeneous systems, Stampede, co-processor



Q. Meng, A. Humphrey, J. Schmidt, M. Berzins. “Investigating Applications Portability with the Uintah DAG-based Runtime System on PetaScale Supercomputers,” SCI Technical Report, No. UUSCI-2013-003, SCI Institute, University of Utah, 2013.

ABSTRACT

Present trends in high performance computing present formidable challenges for applications code using multicore nodes possibly with accelerators and/or co-processors and reduced memory while still attaining scalability. Software frameworks that execute machineindependent applications code using a runtime system that shields users from architectural complexities offer a possible solution. The Uintah framework for example, solves a broad class of large-scale problems on structured adaptive grids using fluid-flow solvers coupled with particle-based solids methods. Uintah executes directed acyclic graphs of computational tasks with a scalable asynchronous and dynamic runtime system for CPU cores and/or accelerators/coprocessors on a node. Uintah's clear separation between application and runtime code has led to scalability increases of 1000x without significant changes to application code. This methodology is tested on three leading Top500 machines; OLCF Titan, TACC Stampede and ALCF Mira using three diverse and challenging applications problems. This investigation of scalability with regard to the different processors and communications performance leads to the overall conclusion that the adaptive DAG-based approach provides a very powerful abstraction for solving challenging multiscale multi-physics engineering problems on some of the largest and most powerful computers available today.

Keywords: Uintah, hybrid parallelism, scalability, parallel, adaptive, MIC, Xeon Phi, heterogeneous systems, Stampede, co-processor



Q. Meng, A. Humphrey, J. Schmidt, M. Berzins. “Investigating Applications Portability with the Uintah DAG-based Runtime System on PetaScale Supercomputers,” In Proceedings of SC13: International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 96:1--96:12. 2013.
ISBN: 978-1-4503-2378-9
DOI: 10.1145/2503210.2503250

ABSTRACT

Present trends in high performance computing present formidable challenges for applications code using multicore nodes possibly with accelerators and/or co-processors and reduced memory while still attaining scalability. Software frameworks that execute machine-independent applications code using a runtime system that shields users from architectural complexities offer a possible solution. The Uintah framework for example, solves a broad class of large-scale problems on structured adaptive grids using fluid-flow solvers coupled with particle-based solids methods. Uintah executes directed acyclic graphs of computational tasks with a scalable asynchronous and dynamic runtime system for CPU cores and/or accelerators/co-processors on a node. Uintah's clear separation between application and runtime code has led to scalability increases of 1000x without significant changes to application code. This methodology is tested on three leading Top500 machines; OLCF Titan, TACC Stampede and ALCF Mira using three diverse and challenging applications problems. This investigation of scalability with regard to the different processors and communications performance leads to the overall conclusion that the adaptive DAG-based approach provides a very powerful abstraction for solving challenging multi-scale multi-physics engineering problems on some of the largest and most powerful computers available today.

Keywords: Blue Gene/Q, GPU, Xeon Phi, adaptive, application, co-processor, heterogeneous systems, hybrid parallelism, parallel, scalability, software, uintah, NETL



Q. Meng, A. Humphrey, J. Schmidt, M. Berzins. “Preliminary Experiences with the Uintah Framework on Intel Xeon Phi and Stampede,” In Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery (XSEDE 2013), San Diego, California, pp. 48:1--48:8. 2013.
DOI: 10.1145/2484762.2484779

ABSTRACT

In this work, we describe our preliminary experiences on the Stampede system in the context of the Uintah Computational Framework. Uintah was developed to provide an environment for solving a broad class of fluid-structure interaction problems on structured adaptive grids. Uintah uses a combination of fluid-flow solvers and particle-based methods, together with a novel asynchronous task-based approach and fully automated load balancing. While we have designed scalable Uintah runtime systems for large CPU core counts, the emergence of heterogeneous systems presents considerable challenges in terms of effectively utilizing additional on-node accelerators and co-processors, deep memory hierarchies, as well as managing multiple levels of parallelism. Our recent work has addressed the emergence of heterogeneous CPU/GPU systems with the design of a Unified heterogeneous runtime system, enabling Uintah to fully exploit these architectures with support for asynchronous, out-of-order scheduling of both CPU and GPU computational tasks. Using this design, Uintah has run at full scale on the Keeneland System and TitanDev. With the release of the Intel Xeon Phi co-processor and the recent availability of the Stampede system, we show that Uintah may be modified to utilize such a co-processor based system. We also explore the different usage models provided by the Xeon Phi with the aim of understanding portability of a general purpose framework like Uintah to this architecture. These usage models range from the pragma based offload model to the more complex symmetric model, utilizing all co-processor and host CPU cores simultaneously. We provide preliminary results of the various usage models for a challenging adaptive mesh refinement problem, as well as a detailed account of our experience adapting Uintah to run on the Stampede system. Our conclusion is that while the Stampede system is easy to use, obtaining high performance from the Xeon Phi co-processors requires a substantial but different investment to that needed for GPU-based systems.

Keywords: MIC, Xeon Phi, adaptive, co-processor, heterogeneous systems, hybrid parallelism, parallel, scalability, stampede, uintah, c-safe



D.C.B. de Oliveira, Z. Rakamaric, G. Gopalakrishnan, A. Humphrey, Q. Meng, M. Berzins. “Crash Early, Crash Often, Explain Well: Practical Formal Correctness Checking of Million-core Problem Solving Environments for HPC,” In Proceedings of the 35th International Conference on Software Engineering (ICSE 2013), pp. (accepted). 2013.

ABSTRACT

While formal correctness checking methods have been deployed at scale in a number of important practical domains, we believe that such an experiment has yet to occur in the domain of high performance computing at the scale of a million CPU cores. This paper presents preliminary results from the Uintah Runtime Verification (URV) project that has been launched with this objective. Uintah is an asynchronous task-graph based problem-solving environment that has shown promising results on problems as diverse as fluid-structure interaction and turbulent combustion at well over 200K cores to date. Uintah has been tested on leading platforms such as Kraken, Keenland, and Titan consisting of multicore CPUs and GPUs, incorporates several innovative design features, and is following a roadmap for development well into the million core regime. The main results from the URV project to date are crystallized in two observations: (1) A diverse array of well-known ideas from lightweight formal methods and testing/observing HPC systems at scale have an excellent chance of succeeding. The real challenges are in finding out exactly which combinations of ideas to deploy, and where. (2) Large-scale problem solving environments for HPC must be designed such that they can be \"crashed early\" (at smaller scales of deployment) and \"crashed often\" (have effective ways of input generation and schedule perturbation that cause vulnerabilities to be attacked with higher probability). Furthermore, following each crash, one must \"explain well\" (given the extremely obscure ways in which an error finally manifests itself, we must develop ways to record information leading up to the crash in informative ways, to minimize offsite debugging burden). Our plans to achieve these goals and to measure our success are described. We also highlight some of the broadly applicable concepts and approaches.

Keywords: Uintah