AXTAR: Mission Design Concept

The Advanced X-ray Timing Array (AXTAR) is a mission concept for X-ray timing of compact objects that combines very large collecting area, broadband spectral coverage, high time resolution, highly flexible scheduling, and an ability to respond promptly to time-critical targets of opportunity. It is optimized for submillisecond timing of bright Galactic X-ray sources in order to study phenomena at the natural time scales of neutron star surfaces and black hole event horizons, thus probing the physics of ultradense matter, strongly curved spacetimes, and intense magnetic fields. AXTAR's main instrument, the Large Area Timing Array (LATA) is a collimated instrument with 2-50 keV coverage and over 3 square meters effective area. The LATA is made up of an array of supermodules that house 2-mm thick silicon pixel detectors. AXTAR will provide a significant improvement in effective area (a factor of 7 at 4 keV and a factor of 36 at 30 keV) over the RXTE PCA. AXTAR will also carry a sensitive Sky Monitor (SM) that acts as a trigger for pointed observations of X-ray transients in addition to providing high duty cycle monitoring of the X-ray sky. We review the science goals and technical concept for AXTAR and present results from a preliminary mission design study.Comment: 19 pages, 10 figures, to be published in Space Telescopes and Instrumentation 2010: Ultraviolet to Gamma Ray, Proceedings of SPIE Volume 773

ProtoEXIST: Advanced Prototype CZT Coded Aperture Telescopes for EXIST

{\it ProtoEXIST1} is a pathfinder for the {\it EXIST-HET}, a coded aperture hard X-ray telescope with a 4.5 m$^2$ CZT detector plane a 90$\times$70 degree field of view to be flown as the primary instrument on the {\it EXIST} mission and is intended to monitor the full sky every 3 h in an effort to locate GRBs and other high energy transients. {\it ProtoEXIST1} consists of a 256 cm$^2$ tiled CZT detector plane containing 4096 pixels composed of an 8$\times$8 array of individual 1.95 cm $\times$ 1.95 cm $\times$ 0.5 cm CZT detector modules each with a 8 $\times$ 8 pixilated anode configured as a coded aperture telescope with a fully coded $10^\circ\times10^\circ$ field of view employing passive side shielding and an active CsI anti-coincidence rear shield, recently completed its maiden flight out of Ft. Sumner, NM on the 9th of October 2009. During the duration of its 6 hour flight on-board calibration of the detector plane was carried out utilizing a single tagged 198.8 nCi Am-241 source along with the simultaneous measurement of the background spectrum and an observation of Cygnus X-1. Here we recount the events of the flight and report on the detector performance in a near space environment. We also briefly discuss {\it ProtoEXIST2}: the next stage of detector development which employs the {\it NuSTAR} ASIC enabling finer (32$\times$32) anode pixilation. When completed {\it ProtoEXIST2} will consist of a 256 cm$^2$ tiled array and be flown simultaneously with the ProtoEXIST1 telescope

Efficient Intra-Rack Resource Disaggregation for HPC Using Co-Packaged DWDM Photonics

The diversity of workload requirements and increasing hardware heterogeneity in emerging high performance computing (HPC) systems motivate resource disaggregation. Resource disaggregation allows compute and memory resources to be allocated individually as required to each workload. However, it is unclear how to efficiently realize this capability and cost-effectively meet the stringent bandwidth and latency requirements of HPC applications. To that end, we describe how modern photonics can be co-designed with modern HPC racks to implement flexible intra-rack resource disaggregation and fully meet the bit error rate (BER) and high escape bandwidth of all chip types in modern HPC racks. Our photonic-based disaggregated rack provides an average application speedup of 11% (46% maximum) for 25 CPU and 61% for 24 GPU benchmarks compared to a similar system that instead uses modern electronic switches for disaggregation. Using observed resource usage from a production system, we estimate that an iso-performance intra-rack disaggregated HPC system using photonics would require 4x fewer memory modules and 2x fewer NICs than a non-disaggregated baseline.Comment: 15 pages, 12 figures, 4 tables. Published in IEEE Cluster 202

Book of Knowledge (BOK) for NASA Electronic Packaging Roadmap

The objective of this document is to update the NASA roadmap on packaging technologies (initially released in 2007) and to present the current trends toward further reducing size and increasing functionality. Due to the breadth of work being performed in the area of microelectronics packaging, this report presents only a number of key packaging technologies detailed in three industry roadmaps for conventional microelectronics and a more recently introduced roadmap for organic and printed electronics applications. The topics for each category were down-selected by reviewing the 2012 reports of the International Technology Roadmap for Semiconductor (ITRS), the 2013 roadmap reports of the International Electronics Manufacturing Initiative (iNEMI), the 2013 roadmap of association connecting electronics industry (IPC), the Organic Printed Electronics Association (OE-A). The report also summarizes the results of numerous articles and websites specifically discussing the trends in microelectronics packaging technologies

MICROELECTRONICS PACKAGING TECHNOLOGY ROADMAPS, ASSEMBLY RELIABILITY, AND PROGNOSTICS

This paper reviews the industry roadmaps on commercial-off-the shelf (COTS) microelectronics packaging technologies covering the current trends toward further reducing size and increasing functionality. Due tothe breadth of work being performed in this field, this paper presents only a number of key packaging technologies. The topics for each category were down-selected by reviewing reports of industry roadmaps including the International Technology Roadmap for Semiconductor (ITRS) and by surveying publications of the International Electronics Manufacturing Initiative (iNEMI) and the roadmap of association connecting electronics industry (IPC). The paper also summarizes the findings of numerous articles and websites that allotted to the emerging and trends in microelectronics packaging technologies. A brief discussion was presented on packaging hierarchy from die to package and to system levels. Key elements of reliability for packaging assemblies were presented followed by reliabilty definition from a probablistic failure perspective. An example was present for showing conventional reliability approach using Monte Carlo simulation results for a number of plastic ball grid array (PBGA). The simulation results were compared to experimental thermal cycle test data. Prognostic health monitoring (PHM) methods, a growing field for microelectronics packaging technologies, were briefly discussed. The artificial neural network (ANN), a data-driven PHM, was discussed in details. Finally, it presented inter- and extra-polations using ANN simulation for thermal cycle test data of PBGA and ceramic BGA (CBGA) assemblies

High Performance Silicon Photonic Interconnected Systems

Advances in data-driven applications, particularly artificial intelligence and deep learning, are driving the explosive growth of computation and communication in today’s data centers and high-performance computing (HPC) systems. Increasingly, system performance is not constrained by the compute speed at individual nodes, but by the data movement between them. This calls for innovative architectures, smart connectivity, and extreme bandwidth densities in interconnect designs. Silicon photonics technology leverages mature complementary metal-oxide-semiconductor (CMOS) manufacturing infrastructure and is promising for low cost, high-bandwidth, and reconfigurable interconnects. Flexible and high-performance photonic switched architectures are capable of improving the system performance. The work in this dissertation explores various photonic interconnected systems and the associated optical switching functionalities, hardware platforms, and novel architectures. It demonstrates the capabilities of silicon photonics to enable efficient deep learning training. We first present field programmable gate array (FPGA) based open-loop and closed-loop control for optical spectral-and-spatial switching of silicon photonic cascaded micro-ring resonator (MRR) switches. Our control achieves wavelength locking at the user-defined resonance of the MRR for optical unicast, multicast, and multiwavelength-select functionalities. Digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) are necessary for the control of the switch. We experimentally demonstrate the optical switching functionalities using an FPGA-based switch controller through both traditional multi-bit DAC/ADC and novel single-wired DAC/ADC circuits. For system-level integration, interfaces to the switch controller in a network control plane are developed. The successful control and the switching functionalitiesachieved are essential for system-level architectural innovations as presented in the following sections. Next, this thesis presents two novel photonic switched architectures using the MRR-based switches. First, a photonic switched memory system architecture was designed to address memory challenges in deep learning. The reconfigurable photonic interconnects provide scalable solutions and enable efficient use of disaggregated memory resources for deep learning training. An experimental testbed was built with a processing system and two remote memory nodes using silicon photonic switch fabrics and system performance improvements were demonstrated. The collective results and existing high-bandwidth optical I/Os show the potential of integrating the photonic switched memory to state-of-the-art processing systems. Second, the scaling trends of deep learning models and distributed training workloads are challenging network capacities in today’s data centers and HPCs. A system architecture that leverages SiP switch-enabled server regrouping is proposed to tackle the challenges and accelerate distributed deep learning training. An experimental testbed with a SiP switch-enabled reconfigurable fat tree topology was built to evaluate the network performance of distributed ring all-reduce and parameter server workloads. We also present system-scale simulations. Server regrouping and bandwidth steering were performed on a large-scale tapered fat tree with 1024 compute nodes to show the benefits of using photonic switched architectures in systems at scale. Finally, this dissertation explores high-bandwidth photonic interconnect designs for disaggregated systems. We first introduce and discuss two disaggregated architectures leveraging extreme high bandwidth interconnects with optically interconnected computing resources. We present the concept of rack-scale graphics processing unit (GPU) disaggregation with optical circuit switches and electrical aggregator switches. The architecture can leverage the flexibility of high bandwidth optical switches to increase hardware utilization and reduce application runtimes. A testbed was built to demonstrate resource disaggregation and defragmentation. In addition, we also present an extreme high-bandwidth optical interconnect accelerated low-latency communication architecture for deep learning training. The disaggregated architecture utilizes comb laser sources and MRR-based cross-bar switching fabrics to enable an all-to-all high bandwidth communication with a constant latency cost for distributed deep learning training. We discuss emerging technologies in the silicon photonics platform, including light source, transceivers, and switch architectures, to accommodate extreme high bandwidth requirements in HPC and data center environments. A prototype hardware innovation - Optical Network Interface Cards (comprised of FPGA, photonic integrated circuits (PIC), electronic integrated circuits (EIC), interposer, and high-speed printed circuit board (PCB)) is presented to show the path toward fast lanes for expedited execution at 10 terabits. Taken together, the work in this dissertation demonstrates the capabilities of high-bandwidth silicon photonic interconnects and innovative architectural designs to accelerate deep learning training in optically connected data center and HPC systems

ToSHI - Towards Secure Heterogeneous Integration: Security Risks, Threat Assessment, and Assurance

The semiconductor industry is entering a new age in which device scaling and cost reduction will no longer follow the decades-long pattern. Packing more transistors on a monolithic IC at each node becomes more difficult and expensive. Companies in the semiconductor industry are increasingly seeking technological solutions to close the gap and enhance cost-performance while providing more functionality through integration. Putting all of the operations on a single chip (known as a system on a chip, or SoC) presents several issues, including increased prices and greater design complexity. Heterogeneous integration (HI), which uses advanced packaging technology to merge components that might be designed and manufactured independently using the best process technology, is an attractive alternative. However, although the industry is motivated to move towards HI, many design and security challenges must be addressed. This paper presents a three-tier security approach for secure heterogeneous integration by investigating supply chain security risks, threats, and vulnerabilities at the chiplet, interposer, and system-in-package levels. Furthermore, various possible trust validation methods and attack mitigation were proposed for every level of heterogeneous integration. Finally, we shared our vision as a roadmap toward developing security solutions for a secure heterogeneous integration