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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Tolerating memory stack failures in multi-stack systems

Memory management circuitry and processes operate to improve reliability of a group of memory stacks, providing that if a memory stack or a portion thereof fails during the product's lifetime, the system may still recover with no errors or data loss. A front-end controller receives a block of data requested to be written to memory, divides the block into sub-blocks, and creates a new redundant reliability sub-block. The sub-blocks are then written to different memory stacks. When reading data from the memory stacks, the front-end controller detects errors indicating a failure within one of the memory stacks, and recovers corrected data using the reliability sub-block. The front-end controller may monitor errors for signs of a stack failure and disable the failed stack.

Mappouras, Georgios↗

MAC: Memory Access Coalescer for 3D-Stacked Memory

Emerging data-intensive applications, such as graph analytics and data mining, exhibit irregular memory access patterns. Research has shown that with these memory-bound applications, traditional cache-based processor architectures, which exploit locality and regular patterns to mitigate the memory-wall issue, are inefficient. Meantime, novel 3D-stacked memory devices, such as Hybrid Mem- ory Cube (HMC) and High Bandwidth Memory (HBM), promise significant increases in bandwidth that appear extremely appealing for memory-bound applications. However, conventional memory interfaces designed for cache-based architectures and JEDEC DDR devices fit poorly with the 3D-stacked memory, which leads to significant under-utilization of the promised high bandwidth. As a response to these issues, in this paper we propose MAC (Memory Access Coalescer), a coalescing unit for the 3D-stacked memory. We discuss the design and implementation of MAC, in the context of a custom designed cache-less architecture targeted at data-intensive, irregular applications. Through a custom simulation infrastructure based on the RISC-V toolchain, we show that MAC achieves a coalescing efficiency of 52.85% on average. It improves the performance of the memory system by 60.73% on average for a large set of irregular workloads.

Wang, Xi↗

HAM: Hotspot-Aware Manager for Improving Communications with 3D-Stacked Memory

merging High-Performance Computing (HPC) workloads, such as graph analytics, machine learning, and big data science, are data-intensive. Data-intensive workloads usually present fine-grained memory accesses with limited or no data locality, and thus incur frequent cache misses and low utilization of memory bandwidth. 3D-stacked memory devices such as Hybrid Memory Cube (HMC) and High Bandwidth Memory (HBM) can provide significantly higher bandwidth than conventional memory modules. However, the traditional interfaces and optimization methods for JEDEC DDR devices do not allow to fully exploit the potential performance of 3D-stacked memory with the massive amount of irregular memory accesses of data-intensive applications. In this paper, we propose a novel Hotspot-Aware Manager (HAM) infrastructure for 3D-stacked memory devices capable of optimizing memory access streams via request aggregation, hotspot detection, and in-memory prefetching. %and an associated hotspot-aware page policy. We present the HAM design and implementation, and simulate it on a system using RISC-V embedded cores with attached HMC devices. We extensively evaluate HAM with over 12 benchmarks and applications representing diverse irregular memory access patterns. The results show that, on average, HAM reduces redundant requests by 37.51\% and increases the prefetch buffer hit rate by 4.2 times, compared to a baseline streaming prefetcher. On the selected benchmark set, HAM provides performance gains of 21.81\% in average (up to 34.28\%) and power savings of 35.07\% over a standard 3D-stacked memory.

Wang, Xi↗

Radiation Tolerant Intelligent Memory Stack (RTIMS)

The Radiation Tolerant Intelligent Memory Stack (RTIMS), suitable for both geostationary and low earth orbit missions, has been developed. The memory module is fully functional and undergoing environmental and radiation characterization. A self-contained flight-like module is expected to be completed in 2006. RTIMS provides reconfigurable circuitry and 2 gigabits of error corrected or 1 gigabit of triple redundant digital memory in a small package. RTIMS utilizes circuit stacking of heterogeneous components and radiation shielding technologies. A reprogrammable field programmable gate array (FPGA), six synchronous dynamic random access memories, linear regulator, and the radiation mitigation circuitries are stacked into a module of 42.7mm x 42.7mm x 13.00mm. Triple module redundancy, current limiting, configuration scrubbing, and single event function interrupt detection are employed to mitigate radiation effects. The mitigation techniques significantly simplify system design. RTIMS is well suited for deployment in real-time data processing, reconfigurable computing, and memory intensive applications.

Ng, Tak-kwong↗

Method and apparatus of integrating memory stacks

A method and apparatus of integrating memory stacks includes providing a first memory die of a first memory technology and a second memory die of a second memory technology. A first logic die is in communication with the first memory die of the first memory technology, and includes a first memory controller including a first memory control function for interpreting requests in accordance with a first protocol for the first memory technology. A second logic die is in communication with the second memory die of the second memory technology and includes a second memory controller including a second memory control function for interpreting requests in accordance with a second protocol for the second memory technology. A memory operation request is received at the first or second memory controller, and the memory operation request is performed in accordance with the associated first memory protocol or the second memory protocol.

Yudanov, Dmitri↗

Module comprising IC memory stack dedicated to and structurally combined with an IC microprocessor chip

A computer module is disclosed in which a stack of glued together IC memory chips is structurally integrated with a microprocessor chip. The memory provided by the stack is dedicated to the microprocessor chip. The microprocessor and its memory stack may be connected either by glue and/or by solder bumps. The solder bumps can perform three functions--electrical interconnection, mechanical connection, and heat transfer. The electrical connections in some versions are provided by wire bonding.

Carson, John C.↗

Thin Co/Ni-based bottom pinned spin-transfer torque magnetic random access memory stacks with high annealing tolerance

Spin-transfer torque magnetic random access memory (STT-MRAM) is considered as a replacement for next generation embedded and stand-alone memory applications. One of the main challenges in the STT-MRAM stack development is the compatibility of the stack with CMOS process flows in which thermal budgets up to 400 °C are applied. In this letter, we report on a perpendicularly magnetized MgO-based tunnel junction (p-MTJ) on a thin Co/Ni perpendicular synthetic antiferromagnetic layer with high annealing tolerance. Tunnel magneto resistance (TMR) loss after annealing occurs when the reference layer loses its perpendicular magnetic anisotropy due to reduction of the CoFeB/MgO interfacial anisotropy. A stable Co/Ni based p-MTJ stack with TMR values of 130% at resistance-area products of 9 Ω μm{sup 2} after 400 °C anneal is achieved via moment control of the Co/Ta/CoFeB reference layer. Thinning of the CoFeB polarizing layer down to 0.8 nm is the key enabler to achieve 400 °C compatibility with limited TMR loss. Thinning the Co below 0.6 nm leads to a loss of the antiferromagnetic interlayer exchange coupling strength through Ru. Insight into the thickness and moment engineering of the reference layer is displayed to obtain the best magnetic properties and high thermal stability for thin Co/Ni SAF-based STT-MRAM stacks.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Radiation-Tolerant Intelligent Memory Stack - RTIMS

This innovation provides reconfigurable circuitry and 2-Gb of error-corrected or 1-Gb of triple-redundant digital memory in a small package. RTIMS uses circuit stacking of heterogeneous components and radiation shielding technologies. A reprogrammable field-programmable gate array (FPGA), six synchronous dynamic random access memories, linear regulator, and the radiation mitigation circuits are stacked into a module of 42.7 42.7 13 mm. Triple module redundancy, current limiting, configuration scrubbing, and single- event function interrupt detection are employed to mitigate radiation effects. The novel self-scrubbing and single event functional interrupt (SEFI) detection allows a relatively soft FPGA to become radiation tolerant without external scrubbing and monitoring hardware

Ng, Tak-kwong↗

Analyzing the suitability of contemporary 3D-stacked PIM architectures for HPC scientific applications

Scaling off-chip bandwidth is challenging due to fundamental limitations, such as a fixed pin count and plateauing signaling rates. Recently, vendors have turned to 2.5D and 3D stacking to closely integrate system components. Interestingly, these technologies can integrate a logic layer under multiple memory dies, enabling computing capability inside a memory stack. This trend in stacking is making PIM architectures commercially viable. In this work, we investigate the suitability of offloading kernels in scientific applications onto 3D stacked PIM architectures. We evaluate several hardware constraints resulted from the stacked structure. We perform extensive simulation experiments and in-depth analysis to quantify the impact of application locality in TLBs, data caches, and memory stacks. Our results also identify design optimization areas in software and hardware for HPC scientific applications.

Peng, Ivy Bo↗

Common data buffer

Time-shared interface speeds data processing in distributed computer network. Two-level high-speed scanning approach routes information to buffer, portion of which is reserved for series of "first-in, first-out" memory stacks. Buffer address structure and memory are protected from noise or failed components by error correcting code. System is applicable to any computer or processing language.

Byrne, F.↗

Extreme-bandwidth scalable performance-per-watt GPU architecture

A technique for accessing memory in an accelerated processing device coupled to stacked memory dies is provided herein. The technique includes receiving a memory access request from an execution unit and identifying whether the memory access request corresponds to memory cells of the stacked dies that are considered local to the execution unit or non-local. For local accesses, the access is made “directly”, that is, without using a bus. A control die coordinates operations for such local accesses, activating particular through-silicon-vias associated with the memory cells that include the data for the access. Non-local accesses are made via a distributed cache fabric and an interconnect bus in the control die. Various other features and details are provided below.

97 MATHEMATICS AND COMPUTING↗

Enabling Highly Efficient Capsule Networks Processing Through A PIM-Based Architecture Design

In recent years, the CNNs have achieved great successes in the image processing tasks, e.g., image recognition and object detection. Unfortunately, traditional CNN's classication is found to be easily misled by increasingly complex image features due to the usage of pooling operations, hence unable to preserve accurate position and pose information of the objects. To address this challenge, a novel neural network structure called Capsule Network has been proposed, which introduces equivariance through capsules to signicantly enhance the learning ability for image segmentation and object detection. Due to its requirement of performing a high volume of matrix operations, CapsNets have been generally accelerated on modern GPU platforms that provide highly optimized software library for common deep learning tasks. However, based on our performance characterization on modern GPUs, CapsNets exhibit low effciency due to the special program and execution features of their routing procedure, including massive unshareable intermediate variables and intensive syn- chronizations, which are very dicult to optimize at software level. To address these challenges, we propose a hybrid computing architecture design named PIM-CapsNet. It preserves GPU's on-chip computing capability for accelerating CNN types of layers in CapsNet, while pipelining with an off-chip in-memory acceleration solution that effectively tackles routing procedure's ineffciency by leveraging the processing-in-memory capability of today's 3D stacked memory. Using routing procedure's inherent parallellization feature, our design enables hierarchical improvements on CapsNet inference effciency through minimizing data movement and maximizing parallel processing in memory. Evaluation results demonstrate that our proposed design can achieve substantial improvement on both performance and energy savings for CapsNet inference, with almost zero accuracy loss. The results also suggest good performance scalability in optimizing the routing procedure with increasing network size.

Zhang, Xingyao↗

Processing-in-Memory Enabled Graphics Processors for 3D Rendering

The performance of 3D rendering of Graphics Processing Unit that convents 3D vector stream into 2D frame with 3D image effects significantly impact users’ gaming experience on modern computer systems. Due to the high texture throughput in 3D rendering, main memory bandwidth becomes a critical obstacle for improving the overall rendering performance. 3D stacked memory systems such as Hybrid Memory Cube (HMC) provide opportunities to significantly overcome the memory wall by directly connecting logic controllers to DRAM dies. Based on the observation that texel fetches significantly impact off-chip memory traffic, we propose two architectural designs to enable Processing-In-Memory based GPU for efficient 3D rendering.

Innovative hardware/software co-design↗

PIMS: A Lightweight Processing-in-Memory Accelerator for Stencil Computations

Stencil computation is a classic computational kernel present in many high-performance scientific applications, like image process- ing and partial differential equation solvers (PDE). A stencil compu- tation sweeps over a multi-dimensional grid and repeatedly updates values associated with points using the values from neighboring points. Stencil computations often employ large datasets that ex- ceed cache capacity, leading to excessive accesses to the memory subsystem. As such, 3D stencil computations on large grid sizes are memory-bound. In this paper we present PIMS, an in-memory accelerator for stencil computations. PIMS, implemented in the logic layer of a 3D- stacked memory, exploits the high bandwidth provided by through- silicon vias to reduce redundant memory traffic. Our comprehensive evaluation using three different grid sizes with six categories of orders indicate that the proposed architecture reduces 48.25% of data movement on average and obtains up to 65.55% of bank conflict reduction.

Li, Jie↗

Plated wire memory subsystem

The design, construction, and test history of a 4096 word by 18 bit random access NDRO Plated Wire Memory for use in conjunction with a spacecraft input/output and central processing unit is reported. A technical and functional description is given along with diagrams illustrating layout and systems operation. Test data is shown on the procedures and results of system level and memory stack testing, and hybrid circuit screening. A comparison of the most significant physical and performance characteristics of the memory unit versus the specified requirements is also included.

Carpenter, K. H.↗

Petabyte mass memory system using the Newell Opticel(TM)

A random access system is proposed for digital storage and retrieval of up to a Petabyte of user data. The system is comprised of stacked memory modules using laser heads writing to an optical medium, in a new shirt-pocket-sized optical storage device called the Opticel. The Opticel described is a completely sealed 'black box' in which an optical medium is accelerated and driven at very high rates to accommodate the desired transfer rates, yet in such a manner that wear is virtually eliminated. It essentially emulates a disk, but with storage area up to several orders of magnitude higher. Access time to the first bit can range from a few milliseconds to a fraction of a second, with time to the last bit within a fraction of a second to a few seconds. The actual times are dependent on the capacity of each Opticel, which ranges from 72 Gigabytes to 1.25 Terabytes. Data transfer rate is limited strictly by the head and electronics, and is 15 Megabits per second in the first version. Independent parallel write/read access to each Opticel is provided using dedicated drives and heads. A Petabyte based on the present Opticel and drive design would occupy 120 cubic feet on a footprint of 45 square feet; with further development, it could occupy as little as 9 cubic feet.

Newell, Chester W.↗