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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Massively parallel and universal approximation of nonlinear functions using diffractive processors

Nonlinear computation is essential for a wide range of information processing tasks, yet implementing nonlinear functions using optical systems remains a challenge due to the weak and power-intensive nature of optical nonlinearities. Overcoming this limitation without relying on nonlinear optical materials could unlock unprecedented opportunities for ultrafast and parallel optical computing systems. Here, we demonstrate that large-scale nonlinear computation can be performed using linear optics through optimized diffractive processors composed of passive phase-only surfaces. In this framework, the input variables of nonlinear functions are encoded into the phase of an optical wavefront—e.g., via a spatial light modulator (SLM)—and transformed by an optimized diffractive structure with spatially varying point-spread functions to yield output intensities that approximate a large set of unique nonlinear functions–all in parallel. We provide proof establishing that this architecture serves as a universal function approximator for an arbitrary set of bandlimited nonlinear functions, also covering wavelength-multiplexed nonlinear functions as well as multi-variate and complex-valued functions that are all-optically cascadable. Our analysis also indicates the successful approximation of typical nonlinear activation functions commonly used in neural networks, including the sigmoid, tanh, ReLU (rectified linear unit), and softplus. We numerically demonstrate the parallel computation of one million distinct nonlinear functions, accurately executed at wavelength-scale spatial density at the output of a diffractive optical processor. Furthermore, we experimentally validated this framework using in situ optical learning and approximated 35 unique nonlinear functions in a single shot using a compact setup consisting of an SLM and an image sensor. These results establish diffractive optical processors as a scalable platform for massively parallel universal nonlinear function approximation, paving the way for new capabilities in analog optical computing based on linear materials.

Rahman, Md Sadman Sakib [University of California,↗
DOE OSTI2012

NEAMS Update: Quarterly Report for October - December 2011

The Advanced Modeling and Simulation Office within the DOE Office of Nuclear Energy (NE) has been charged with revolutionizing the design tools used to build nuclear power plants during the next 10 years. To accomplish this, the DOE has brought together the national laboratories, U.S. universities, and the nuclear energy industry to establish the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program. The mission of NEAMS is to modernize computer modeling of nuclear energy systems and improve the fidelity and validity of modeling results using contemporary software environments and high-performance computers. NEAMS will create a set of engineering-level codes aimed at designing and analyzing the performance and safety of nuclear power plants and reactor fuels. The truly predictive nature of these codes will be achieved by modeling the governing phenomena at the spatial and temporal scales that dominate the behavior. These codes will be executed within a simulation environment that orchestrates code integration with respect to spatial meshing, computational resources, and execution to give the user a common 'look and feel' for setting up problems and displaying results. NEAMS is building upon a suite of existing simulation tools, including those developed by the federal Scientific Discovery through Advanced Computing and Advanced Simulation and Computing programs. NEAMS also draws upon existing simulation tools for materials and nuclear systems, although many of these are limited in terms of scale, applicability, and portability (their ability to be integrated into contemporary software and hardware architectures). NEAMS investments have directly and indirectly supported additional NE research and development programs, including those devoted to waste repositories, safeguarded separations systems, and long-term storage of used nuclear fuel. NEAMS is organized into two broad efforts, each comprising four elements. The quarterly highlights October-December 2011 are: (1) Version 1.0 of AMP, the fuel assembly performance code, was tested on the JAGUAR supercomputer and released on November 1, 2011, a detailed discussion of this new simulation tool is given; (2) A coolant sub-channel model and a preliminary UO{sub 2} smeared-cracking model were implemented in BISON, the single-pin fuel code, more information on how these models were developed and benchmarked is given; (3) The Object Kinetic Monte Carlo model was implemented to account for nucleation events in meso-scale simulations and a discussion of the significance of this advance is given; (4) The SHARP neutronics module, PROTEUS, was expanded to be applicable to all types of reactors, and a discussion of the importance of PROTEUS is given; (5) A plan has been finalized for integrating the high-fidelity, three-dimensional reactor code SHARP with both the systems-level code RELAP7 and the fuel assembly code AMP. This is a new initiative; (6) Work began to evaluate the applicability of AMP to the problem of dry storage of used fuel and to define a relevant problem to test the applicability; (7) A code to obtain phonon spectra from the force-constant matrix for a crystalline lattice has been completed. This important bridge between subcontinuum and continuum phenomena is discussed; (8) Benchmarking was begun on the meso-scale, finite-element fuels code MARMOT to validate its new variable splitting algorithm; (9) A very computationally demanding simulation of diffusion-driven nucleation of new microstructural features has been completed. An explanation of the difficulty of this simulation is given; (10) Experiments were conducted with deformed steel to validate a crystal plasticity finite-element code for bodycentered cubic iron; (11) The Capability Transfer Roadmap was completed and published as an internal laboratory technical report; (12) The AMP fuel assembly code input generator was integrated into the NEAMS Integrated Computational Environment (NiCE). More details on the planned NEAMS computing environment is given; and (13) The NEAMS program website (neams.energy.gov) is nearly ready to launch.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Parallel Programming in MCNP6

Monte Carlo N-Particle (MCNP)1 is a general-purpose Monte Carlo particle transport code developed by Los Alamos National Laboratory (LANL). To efficiently handle long simulations, MCNP version 6 (MCNP6) supports parallel execution using two primary programming models: • Shared-memory task-based threading using OpenMP (Open Multi-Processing), and • Distributed-memory calculations using MPI (Message Passing Interface). The OpenMP and MPI programming models enable MCNP6 to scale from desktop systems to high-performance computing (HPC) clusters, allowing users to run MCNP in one of three parallel modes: • OpenMP-only, • MPI-only, and • Hybrid (MPI + OpenMP). The choice of parallelization mode depends on the underlying computer architecture and the characteristics of the simulation problem.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

Using neural networks and Dyna algorithm for integrated planning, reacting and learning in systems

The traditional AI answer to the decision making problem for a robot is planning. However, planning is usually CPU-time consuming, depending on the availability and accuracy of a world model. The Dyna system generally described in earlier work, uses trial and error to learn a world model which is simultaneously used to plan reactions resulting in optimal action sequences. It is an attempt to integrate planning, reactive, and learning systems. The architecture of Dyna is presented. The different blocks are described. There are three main components of the system. The first is the world model used by the robot for internal world representation. The input of the world model is the current state and the action taken in the current state. The output is the corresponding reward and resulting state. The second module in the system is the policy. The policy observes the current state and outputs the action to be executed by the robot. At the beginning of program execution, the policy is stochastic and through learning progressively becomes deterministic. The policy decides upon an action according to the output of an evaluation function, which is the third module of the system. The evaluation function takes the following as input: the current state of the system, the action taken in that state, the resulting state, and a reward generated by the world which is proportional to the current distance from the goal state. Originally, the work proposed was as follows: (1) to implement a simple 2-D world where a 'robot' is navigating around obstacles, to learn the path to a goal, by using lookup tables; (2) to substitute the world model and Q estimate function Q by neural networks; and (3) to apply the algorithm to a more complex world where the use of a neural network would be fully justified. In this paper, the system design and achieved results will be described. First we implement the world model with a neural network and leave Q implemented as a look up table. Next, we use a lookup table for the world model and implement the Q function with a neural net. Time limitations prevented the combination of these two approaches. The final section discusses the results and gives clues for future work.

Lima, Pedro↗
NASA NTRS1983

Array processor architecture

A high speed parallel array data processing architecture fashioned under a computational envelope approach includes a data base memory for secondary storage of programs and data, and a plurality of memory modules interconnected to a plurality of processing modules by a connection network of the Omega gender. Programs and data are fed from the data base memory to the plurality of memory modules and from hence the programs are fed through the connection network to the array of processors (one copy of each program for each processor). Execution of the programs occur with the processors operating normally quite independently of each other in a multiprocessing fashion. For data dependent operations and other suitable operations, all processors are instructed to finish one given task or program branch before all are instructed to proceed in parallel processing fashion on the next instruction. Even when functioning in the parallel processing mode however, the processors are not locked-step but execute their own copy of the program individually unless or until another overall processor array synchronization instruction is issued.

Barnes, George H.↗
NASA NTRS1995

Algorithms for parallel flow solvers on message passing architectures

The purpose of this project has been to identify and test suitable technologies for implementation of fluid flow solvers -- possibly coupled with structures and heat equation solvers -- on MIMD parallel computers. In the course of this investigation much attention has been paid to efficient domain decomposition strategies for ADI-type algorithms. Multi-partitioning derives its efficiency from the assignment of several blocks of grid points to each processor in the parallel computer. A coarse-grain parallelism is obtained, and a near-perfect load balance results. In uni-partitioning every processor receives responsibility for exactly one block of grid points instead of several. This necessitates fine-grain pipelined program execution in order to obtain a reasonable load balance. Although fine-grain parallelism is less desirable on many systems, especially high-latency networks of workstations, uni-partition methods are still in wide use in production codes for flow problems. Consequently, it remains important to achieve good efficiency with this technique that has essentially been superseded by multi-partitioning for parallel ADI-type algorithms. Another reason for the concentration on improving the performance of pipeline methods is their applicability in other types of flow solver kernels with stronger implied data dependence. Analytical expressions can be derived for the size of the dynamic load imbalance incurred in traditional pipelines. From these it can be determined what is the optimal first-processor retardation that leads to the shortest total completion time for the pipeline process. Theoretical predictions of pipeline performance with and without optimization match experimental observations on the iPSC/860 very well. Analysis of pipeline performance also highlights the effect of uncareful grid partitioning in flow solvers that employ pipeline algorithms. If grid blocks at boundaries are not at least as large in the wall-normal direction as those immediately adjacent to them, then the first processor in the pipeline will receive a computational load that is less than that of subsequent processors, magnifying the pipeline slowdown effect. Extra compensation is needed for grid boundary effects, even if all grid blocks are equally sized.

Vanderwijngaart, Rob F.↗
NASA NTRS1999

Automated Testing Experience of the Linear Aerospike SR-71 Experiment (LASRE) Controller

System controllers must be fail-safe, low cost, flexible to software changes, able to output health and status words, and permit rapid retest qualification. The system controller designed and tested for the aerospike engine program was an attempt to meet these requirements. This paper describes (1) the aerospike controller design, (2) the automated simulation testing techniques, and (3) the real time monitoring data visualization structure. Controller cost was minimized by design of a single-string system that used an off-the-shelf 486 central processing unit (CPU). A linked-list architecture, with states (nodes) defined in a user-friendly state table, accomplished software changes to the controller. Proven to be fail-safe, this system reported the abort cause and automatically reverted to a safe condition for any first failure. A real time simulation and test system automated the software checkout and retest requirements. A program requirement to decode all abort causes in real time during all ground and flight tests assured the safety of flight decisions and the proper execution of mission rules. The design also included health and status words, and provided a real time analysis interpretation for all health and status data.

Larson, Richard R.↗
NASA NTRS2007

PPC750 Performance Monitor

The PPC750 Performance Monitor (Perfmon) is a computer program that helps the user to assess the performance characteristics of application programs running under the Wind River VxWorks real-time operating system on a PPC750 computer. Perfmon generates a user-friendly interface and collects performance data by use of performance registers provided by the PPC750 architecture. It processes and presents run-time statistics on a per-task basis over a repeating time interval (typically, several seconds or minutes) specified by the user. When the Perfmon software module is loaded with the user s software modules, it is available for use through Perfmon commands, without any modification of the user s code and at negligible performance penalty. Per-task run-time performance data made available by Perfmon include percentage time, number of instructions executed per unit time, dispatch ratio, stack high water mark, and level-1 instruction and data cache miss rates. The performance data are written to a file specified by the user or to the serial port of the computer

Meyer, Donald↗
NASA NTRS2014

Ground Operations Autonomous Control and Integrated Health Management

An intelligent autonomous control capability has been developed and is currently being validated in ground cryogenic fluid management operations. The capability embodies a physical architecture consistent with typical launch infrastructure and control systems, augmented by a higher level autonomous control (AC) system enabled to make knowledge-based decisions. The AC system is supported by an integrated system health management (ISHM) capability that detects anomalies, diagnoses causes, determines effects, and could predict future anomalies. AC is implemented using the concept of programmed sequences that could be considered to be building blocks of more generic mission plans. A sequence is a series of steps, and each executes actions once conditions for the step are met (e.g. desired temperatures or fluid state are achieved). For autonomous capability, conditions must consider also health management outcomes, as they will determine whether or not an action is executed, or how an action may be executed, or if an alternative action is executed instead. Aside from health, higher level objectives can also drive how a mission is carried out. The capability was developed using the G2 software environment (www.gensym.com) augmented by a NASA Toolkit that significantly shortens time to deployment. G2 is a commercial product to develop intelligent applications. It is fully object oriented. The core of the capability is a Domain Model of the system where all elements of the system are represented as objects (sensors, instruments, components, pipes, etc.). Reasoning and decision making can be done with all elements in the domain model. The toolkit also enables implementation of failure modes and effects analysis (FMEA), which are represented as root cause trees. FMEA's are programmed graphically, they are reusable, as they address generic FMEA referring to classes of subsystems or objects and their functional relationships. User interfaces for integrated awareness by operators have been created.

Figueroa, Fernando↗
NASA NTRSDate not supplied

Risks of Increased Earth Independence

As human space exploration begins to extend beyond the immediate vicinity of Earth, the ability of expertise on the ground to support operations will progressively decrease. Ground control expertise has been the primary countermeasure preventing loss of life and mission over the past sixty years and it will be gradually stripped away as expeditions reach further into space. The large, flexible and adaptive teams of experts on the ground, provide not only engineering analysis and problem-solving but also greatly increased work capacity. Monitoring of the large and fast moving stream of telemetry data is carried out around the clock by 20-30 flight controllers per shift. Analysis of that data and troubleshooting is carried out by an additional 50-100 engineers per shift. Artificial intelligence capabilities will need to be part of the solution but will not the entire solution. As progress continues to be made on intelligent systems, especially those for use in complex, dynamic environments where humans will remain a part of the activity, there is an ever increasing need to focus on how those systems will interact with the humans. Although capabilities such as natural language processing and facial recognition have become common place, even basic aspects of problem-solving, causal reasoning and generative decision-making remain well-beyond of our current capabilities. Advanced data visualization, procedure execution support, and new training approaches will be needed to close the gap between what is currently provided by experts on the ground and what the crew will need to do in increasingly autonomous ways with greater distance from Earth.

human-systems integration architecture↗
NASA NTRS1991

Space transfer vehicle concepts and requirements. Volume 1: Executive summary

The objectives of the Space Transfer Vehicle (STV) Concepts and Requirements studies were to provide sensitivity data on usage, economics, and technology associated with new space transportation systems. The study was structured to utilize data on the emerging launch vehicles, the latest mission scenarios, and Space Exploration Initiative (SEI) payload manifesting and schedules, to define a flexible, high performance, cost effective, evolutionary space transportation system for NASA. Initial activities were to support the MSFC effort in the preparation of inputs to the 90 Day Report to the National Space Council (NSC). With the results of this study establishing a point-of-departure for continuing the STV studies in 1990, additional options and mission architectures were defined. The continuing studies will update and expand the parametrics, assess new cargo and manned ETO vehicles, determine impacts on the redefined Phase 0 Space Station Freedom, and to develop a design that encompasses adequate configuration flexibility to ensure compliance with on-going NASA study recommendations with major system disconnects. In terms of general requirements, the objectives of the STV system and its mission profiles will address crew safety and mission success through a failure-tolerant and forgiving design approach. These objectives were addressed through the following: engine-out capability for all mission phases; built-in-test for vehicle health monitoring to allow testing of all critical functions such as, verification of lunar landing and ascent engines before initiating the landing sequence; critical subsystems will have multiple strings for redundancy plus adequate supplies of onboard spares for removal and replacement of failed items; crew radiation protection; and trajectories that optimize lunar and Mars performance and flyby abort capabilities.

Source record↗
DOE OSTI2014

Optimizing Sparse Matrix-Multiple Vectors Multiplication for Nuclear Configuration Interaction Calculations

Obtaining highly accurate predictions on the properties of light atomic nuclei using the configuration interaction (CI) approach requires computing a few extremal Eigen pairs of the many-body nuclear Hamiltonian matrix. In the Many-body Fermion Dynamics for nuclei (MFDn) code, a block Eigen solver is used for this purpose. Due to the large size of the sparse matrices involved, a significant fraction of the time spent on the Eigen value computations is associated with the multiplication of a sparse matrix (and the transpose of that matrix) with multiple vectors (SpMM and SpMM-T). Existing implementations of SpMM and SpMM-T significantly underperform expectations. Thus, in this paper, we present and analyze optimized implementations of SpMM and SpMM-T. We base our implementation on the compressed sparse blocks (CSB) matrix format and target systems with multi-core architectures. We develop a performance model that allows us to understand and estimate the performance characteristics of our SpMM kernel implementations, and demonstrate the efficiency of our implementation on a series of real-world matrices extracted from MFDn. In particular, we obtain 3-4 speedup on the requisite operations over good implementations based on the commonly used compressed sparse row (CSR) matrix format. The improvements in the SpMM kernel suggest we may attain roughly a 40% speed up in the overall execution time of the block Eigen solver used in MFDn.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The Case for Co-Designing Model Architectures with Hardware

While GPUs are responsible for training the vast majority of state-of-the-art deep learning models, the implications of their architecture are often overlooked when designing new deep learning (DL) models. As a consequence, modifying a DL model to be more amenable to the target hardware can significantly improve the runtime performance of DL training and inference. In this paper, we provide a set of guidelines for users to maximize the runtime performance of their transformer models. These guidelines have been created by carefully considering the impact of various model hyperparameters controlling model shape on the efficiency of the underlying computation kernels executed on the GPU. We find the throughput of models with “efficient” model shapes is up to 39% higher while preserving accuracy compared to models with a similar number of parameters but with unoptimized shapes.

Yin, Junqi↗
DOE OSTI2018

Sandia Cloud Forensics and Incident Response Platform v 1.0

As systems and devices become virtualized and deployed in the cloud, the hypervisor becomes an increasingly appropriate place to collect performance data, system state, system landscape, function calls, transaction traces, and other characteristics. We developed a method by which an introspection application may be coupled with a hypervisor to “reach into” the VM with minimal intrusiveness to collect data critical to the reconstruction of events, files, and operations. Such a capability is required to take advantage of the hypervisor as an instrumentation platform and to integrate that data with more traditional collection mechanisms. The concept of a VM serviced by a lightweight hypervisor is a relatively new paradigm for forensic practitioners. Traditional forensic techniques, based on assumptions that the filesystem was directly interacting with the hardware through an abstraction, afforded the forensic practitioner the assumption that there was nothing controlling the application below the filesystem. This is not the case when using virtualized technologies. Hypervisors can covertly monitor, introspect and interact with the guest in a transparent fashion. The problems of storage and collection of actionable data are exhausting. The current challenge is most hypervisors do not expose a useful application programming interface (API) at a sufficient level to do transparent, fine-grained and customizable introspection. Scalable VM instrumentation and introspection at an in-depth level requires fast handling of events, as well as direct access to VM state. Furthermore, deep introspection benefits greatly from the ability to gather data from the hardware during the VM’s exit to the hypervisor. All of this requires identical access to the system as the hypervisor itself; improper use of this ability could easily cause system instability. It is for this reason we believe that the hypervisor developers have been hesitant to grant this much control through their APIs. However, our approach leverages other means to collect and monitor the guests in a targeted fashion. Virtual machine introspection (VMI) is a technique used to monitor the runtime state of a system-level virtual machine. The runtime state can be may include processor registers, memory, disk, network, and any other hardware-level events A review of research literature and current VMI technologies exposed several limitations and tradeoffs in VMI approaches, including: the use of in-guest agents; kernel to user space transitions (dramatically slowing down processing); VMI tool pre-configuration requirements; hypervisor version lock-in or source code patching; reliance on operating system symbols; limited processor features due to hypervisor (even if the hardware could do more). To address these constraints, a VMI tool was envisioned to provide the cloud forensic capabilities while having as few of these limitations as possible. The Kernel-based Virtual Machine Introspection (KVMi) tool was developed for hypervisors on Intel’s x86-64 architecture. To meet performance, scoping and use-case demands, the follow criteria were applied to KVMi to support live, forensic data collection: • Shall not require in-guest agents. • Shall work with any recent version of modern hypervisors. • Shall introspect upon any guest (VM) running modern versions of Windows, Linux and OS X. • Shall have the ability to find and track operating system artifacts • Shall not require operating system symbol files. • Shall be able to fully handle VM-exits, bypassing execution of the hypervisor if necessary, to facilitate new features the hypervisor may not support. • Shall be compilable/loadable on a running system with standard build tools.

Stout, WilliamM.S.↗
NASA NTRS1987

SOLON: An autonomous vehicle mission planner

The State-Operator Logic Machine (SOLON) Planner provides an architecture for effective real-time planning and replanning for an autonomous vehicle. The highlights of the system, which distinguish it from other AI-based planners that have been designed previously, are its hybrid application of state-driven control architecture and the use of both schematic representations and logic programming for the management of its knowledge base. SOLON is designed to provide multiple levels of planning for a single autonomous vehicle which is supplied with a skeletal, partially-specified mission plan at the outset of the vehicle's operations. This mission plan consists of a set of objectives, each of which will be decomposable by the planner into tasks. These tasks are themselves comparatively complex sets of actions which are executable by a conventional real-time control system which does not perform planning but which is capable of making adjustments or modifications to the provided tasks according to constraints and tolerances provided by the Planner. The current implementation of the SOLON is in the form of a real-time simulation of the Planner module of an Intelligent Vehicle Controller (IVC) on-board an autonomous underwater vehicle (AUV). The simulation is embedded within a larger simulator environment known as ICDS (Intelligent Controller Development System) operating on a Symbolics 3645/75 computer.

Dudziak, M. J.↗
NASA NTRS2006

A Model-Driven Architecture Approach for Modeling, Specifying and Deploying Policies in Autonomous and Autonomic Systems

Autonomic Computing (AC), self-management based on high level guidance from humans, is increasingly gaining momentum as the way forward in designing reliable systems that hide complexity and conquer IT management costs. Effectively, AC may be viewed as Policy-Based Self-Management. The Model Driven Architecture (MDA) approach focuses on building models that can be transformed into code in an automatic manner. In this paper, we look at ways to implement Policy-Based Self-Management by means of models that can be converted to code using transformations that follow the MDA philosophy. We propose a set of UML-based models to specify autonomic and autonomous features along with the necessary procedures, based on modification and composition of models, to deploy a policy as an executing system.

Pena, Joaquin↗
NASA NTRS2005

Mars Exploration Rover Entry, Descent, and Landing: A Thermal Perspective

Perhaps the most challenging mission phase for the Mars Exploration Rovers was the Entry, Descent, and Landing (EDL). During this phase, the entry vehicle attached to its cruise stage was transformed into a stowed tetrahedral Lander that was surrounded by inflated airbags through a series of complex events. There was only one opportunity to successfully execute an automated command sequence without any possible ground intervention. The success of EDL was reliant upon the system thermal design: 1) to thermally condition EDL hardware from cruise storage temperatures to operating temperature ranges; 2) to maintain the Rover electronics within operating temperature ranges without the benefit of the cruise single phase cooling loop, which had been evacuated in preparation for EDL; and 3) to maintain the cruise stage propulsion components for the critical turn to entry attitude. Since the EDL architecture was inherited from Mars Pathfinder (MPF), the initial EDL thermal design would be inherited from MPF. However, hardware and implementation differences from MPF ultimately changed the MPF inheritance approach for the EDL thermal design. With the lack of full inheritance, the verification and validation of the EDL thermal design took on increased significance. This paper will summarize the verification and validation approach for the EDL thermal design along with applicable system level thermal testing results as well as appropriate thermal analyses. In addition, the lessons learned during the system-level testing will be discussed. Finally, the in-flight EDL experiences of both MER-A and -B missions (Spirit and Opportunity, respectively) will be presented, demonstrated how lessons learned from Spirit were applied to Opportunity.

thermal↗
NASA NTRS2018

IV&V Planning & Execution Initiative

Independent verification and validation (IV&V) is a systems engineering discipline which seeks to provide confidence that mission-critical software-dependent systems will operate safely and achieve all mission objectives. In order to optimize application of IV&V resources, it is necessary to identify specific assurance objectives that are most likely to reveal difficulty and therefore to increase confidence. Software assurance literature deals predominantly with the code itself. However, our experience is that the most significant software-related issues are discovered via analysis of other system artifacts such as operations concepts, requirements and design. Consequently, it is desirable to, when assessing risk and defining assurance objectives, consider all facets of the software system architecture. We describe in this presentation progress and lessons learned from an IV&V capability development initiative to enhance the IV&V project planning process using all available architecture information.

Risk↗