US DOD’s JUMP program to develop high performance, energy efficient and secure microelectronics for dominance in future Battlefield Internet of Things
The Joint University Microelectronics Program (“JUMP”), is a collaborative effort between the Department of Defense, U.S. universities and the industrial participants with a goal to substantially increase the performance, efficiency, and capabilities of broad classes of electronics systems for both commercial and military applications.
The collaborative, multidisciplinary, multi-university consortium will support long-term research focused on high performance, energy efficient microelectronics for end-to-end sensing and actuation, signal and information processing, communication, computing, and storage solutions that are cost-effective and secure.
These research and development efforts should provide the Department of Defense with an unmatched technological edge in advanced radar, communications, and weapons systems, and provide the U.S. economy with unique information technology and processing capabilities critical to commercial competitiveness and future economic growth.
The Consortium seeks to address existing and emerging challenges in electronics and systems technologies by concentrating resources on high-risk, high-payoff, long-range innovative research to accelerate the productivity growth and performance enhancement of electronic technologies and circuits, sub-systems, and multi-scale systems. To this end, JUMP is focused on exploratory research on an 8-12 year time horizon that is anticipated to lead to defense and commercial opportunities in the 2025-2030 timeframe.
Research will continue for five years and commence in January 2018, with funding support coming from industry and government partners. Total JUMP funding for the five-year period will be in excess of $150M, including funds committed by DARPA (Defense Advanced Research Projects Agency, www.darpa.mil), IBM Corporation, Northrop Grumman Corporation, Micron Technology, Inc., Intel Corporation, EMD Performance Materials (a Merck KGaA affiliate), Analog Devices Inc., Raytheon Company, Taiwan Semiconductor Manufacturing Company Ltd., and Lockheed Martin Corporation.
Current planning supports six research themes across six JUMP centers and utilizes vertical and horizontal centers to capture the intersections of ideas. While the vertical research centers emphasize breakthrough technologies and products, Horizontal research centers will drive foundational developments in a specific discipline, and create disruptive breakthroughs in areas of interest.
“Vertical” Application-Focused Centers
“Vertical” research Centers emphasize application-oriented goals that focus on key issues facing the industry by addressing the full span of multi-disciplined science and engineering required to achieve breakthrough technologies and products. The centers will create complex systems with capabilities well beyond those available today and that will be ready for transfer in the 5 year time frame and implementation in ~10 years. Technology areas of interest for the JUMP “vertical” Centers include:
RF to THz Sensor and Communication Systems.
This theme seeks research in two general, synergistic application areas – RF Sensors and RF Communications Systems – that operate at microwave, millimeter wave or THz frequencies in support of consumer, military, industrial, scientific and medical applications. System examples may include radar, communication, reconnaissance and/or mmwave/THz imaging.
As an example, it is envisioned that future RF sensor systems will require novel, energy-efficient devices, circuits, algorithms, and architectures for adaptively sensing the environment, extracting/manipulating/processing information, and autonomously reacting/responding to the information.
Another example is cognitive communication systems – systems which will operate in complicated radio environments with interference, jamming and rapidly changing network topology, will obtain (sense) information about their environment (aware of their environment and the available resources ) and will dynamically adjust their operation (e.g., efficient spectrum use, interference mitigation, spectrum prioritization) to provide required services to end users.
These future systems should also have Agility, reconfigurable, adaptive, multi-function, multi-mode, self-calibrating sensors with increased degrees of freedom for efficient use of EM spectrum (including: spectrum agility, instantaneous bandwidth/ waveform agility, (very) wide bandwidth, high dynamic range). Autonomous operation and decision making is also desirable. (e.g., embedded real-time learning, ability to recognize threat scenarios, ability to do local-processing before transmitting the data/information)
Super-linear communication links (enabling high modulation formats) and integrated communications components for IoT and distributed sensor systems that enable ultra-low power, high data rate, long-range sensor communications with high linearity in up/down conversion
To address these applications, centers focusing on this vertically integrated application must drive breakthrough research in materials, devices, components, circuits, integration and packaging, connectivity, architectures (e.g., subsystems/arrays), and algorithms that are aimed at efficiently generating, modulating, manipulating, processing (mainly in or very closely coupled to the RF/mm wave /THz domain), communicating (transmitting) and sensing/detecting radiated signals.
Distributed Computing and Networking.
Importantly, new application requirements coupled with physics-based implementation constraints on latency and energy call for novel architectural solutions to computing-at-scale, requiring innovations in interconnect and networking at all levels, from on-chip to between datacenters.
The purpose of this theme is to explore the challenges of extremely large-scale distributed architectures. Novel, multi-tier, wired and wirelessly-connected heterogeneous systems are expected; tiers may be sensor/actuator, aggregation, cloud/datacenter, or combinations thereof. All tiers are expected to be highly scalable, and heterogeneity is expected both within and across the tiers.
Dramatic advances over today’s systems (cloud, mobile, etc.) and capabilities are required. Proposers are expected to define and tackle a grand challenge in the Distributed Computing and Networking space; the grand challenge should focus attention on research issues that would benefit a broad range of civilian and defense applications (e.g. society-scale digital currencies; battlefield command-and-control in denied environments; smart grid optimization; disaster management in digital cities .
It also calls for Development of new distributed computing systems for new applications besides IoT and big data. Novel computing architectures to reduce the energy and time used to process and transport data, locally and remotely for hyperspectral sensing, data fusion, decision making, and safe effector actuation in a distributed computing environment. Provide cooperative and coordinated distributed-system concepts that are scalable and function in communications-challenged environments (where both wired and wireless environments are not guaranteed to be available, reliable, or safe); address approaches to allow for proper operation in isolation environments, and that can intelligently synchronize when communications are restored, including only partial restoration
This theme will primarily focus on digital computing. All tiers are expected to be highly scalable, and heterogeneity is expected both within and across the tiers.
The Cognitive Computing theme aims to create cognitive computing systems that can learn at scale, perform reasoning and decision making with purpose, and interact with humans naturally and in real-time. Realizing these novel systems may heavily leverage non-traditional computing methods, such as analog computing, stochastic computing, Shannon inspired computing, approximate computing, and bio/brain-inspired models including neuromorphic computing for a broad application space.
This theme seeks to explore multiple approaches for building machine intelligent systems with both cognitive and autonomous characteristics. Such systems can be solely non-traditional, solely von-Neumann or a combination of both elements. A key goal is creating systems that, without explicit objectives, operate in the natural world on their own by forming and extending models of the world they perceive around them, and by interacting with local human decision makers and with global distributed intelligent networks in performing actions to achieve useful yet complex goals.
A full-system approach is required to achieve the goals of this theme. In addition, the proposed research should address the technology advances that are needed for fundamental improvements in performance, capabilities, and energy efficiency through improvements in programming paradigms, algorithms, architectures, circuits, and device technologies.
Intelligent Memory and Storage.
Advances in information technology have pushed data generation rates and quantities to a point where memory and storage are the focal point of optimization of computer systems. Transfer energy, latency and bandwidth are critical to performance and energy efficiency of these systems. The solutions to many modern computing problems involve many-many relationships that can benefit from high cross-sectional bandwidth of the distributed computing platform. As an example, large scale graph analytics involve high cross-data-set evaluation of numerous neighbor relationships ultimately demanding high the highest possible cross-sectional bandwidth of the system.
This research vector seeks a holistic, vertically-integrated, approach to high-performance Intelligent Storage systems encompassing the operating system, programming models, memory management technologies, and a prototype system architecture. A primary focus area for this center will be in establishing an operating system framework allowing run-time optimization of the system based on system configuration preferences, programmer preferences, and the current state of the system.
New Architecture and Programming paradigms, Self-optimizing Systems Allowing for Appropriate Programmer Control. 10X more power efficient computing platform scalable from high performance application processors to less-demanding processors for IoT/sensors/etc. with cost awareness. Small, Probably Low Cost, Compute+Memory+Sensor Node Capable of making Basic Decisions/observations and Reporting to a Larger System.
The technology can span across material, devices, packaging, circuits/systems techniques, computer architecture including but not limited to heterogeneous computing, memory technology (including NVM) and high-speed interface (on-chip and off-chip), etc.
“Horizontal” Disciplinary-Focused Centers
“Horizontal” research centers will drive foundational developments in a specific discipline, or set of like-minded disciplines, will build expertise in and around key disciplinary building blocks, and create disruptive breakthroughs in areas of interest to JUMP sponsors. These centers have a mission to identify and accelerate progress for new technologies that look beyond traditional CMOS. Proposers are expected to define a set of key metrics that their center will use to benchmark and drive efforts in their research space. Technology areas of interest for our JUMP “horizontal” Centers include:
Advanced Architecture and Algorithms.
Today’s system architectures, including distributed clusters, symmetric multiprocessors (SMPs), and communications systems, are generally comprised of homogeneous hardware components that are difficult to modify once deployed. Heterogeneous architectures and elements, such as accelerators, will increasingly be needed to enable scaling of performance, energy efficiency, and cost.
This theme must lay the foundations for new paradigms in scalable, heterogeneous architectures, co-designed with algorithmic implications and vice versa. A major goal of this theme is to address the design and integration challenges of a broad variety of accelerators, both on-chip and off-chip, along with the algorithmic and system software innovations needed to readily incorporate them into both existing and future systems (e.g, information processing, communications, sensing/imaging, etc.).
Centers should address the design and integration challenges of: systems composed of on-chip and off-chip accelerators, computation in and/or near data, and non-traditional computing. Employing novel co-design to bridge the gap between architectures and algorithms for optimization, combinatorics, computational geometry, distributed systems, learning theory, online algorithms, cryptography, etc. are within scope. Benchmarking of the novel architectures is expected. Modeling and software innovations should be used to remove barriers to hardware implementation or mass adoption.
Advanced Devices, Packaging, and Materials.
This theme will address advanced active and passive devices, interconnect, and packaging concepts, based on physics of new materials and unconventional syntheses.
This technology is needed to enable the next breakthrough paradigms in computation (including analog) and information sensing, processing, and storage that will provide further scaling and energy efficiencies. These new materials and devices will provide new functionalities and properties that can augment and/or surpass conventional semiconductor technologies, and will potentially enable novel 3D options. Material development, device demonstration and viable process integration are all within scope. Experimental demonstrations as well as ab-initio material and process modeling are expected.
Energy harvesting and energy storage devices: novel materials for high efficiency energy harvesting, supercapacitors, integrated batteries, power delivery
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