Matching Items (87)
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Description
In recent years we have witnessed a shift towards multi-processor system-on-chips (MPSoCs) to address the demands of embedded devices (such as cell phones, GPS devices, luxury car features, etc.). Highly optimized MPSoCs are well-suited to tackle the complex application demands desired by the end user customer. These MPSoCs incorporate a

In recent years we have witnessed a shift towards multi-processor system-on-chips (MPSoCs) to address the demands of embedded devices (such as cell phones, GPS devices, luxury car features, etc.). Highly optimized MPSoCs are well-suited to tackle the complex application demands desired by the end user customer. These MPSoCs incorporate a constellation of heterogeneous processing elements (PEs) (general purpose PEs and application-specific integrated circuits (ASICS)). A typical MPSoC will be composed of a application processor, such as an ARM Coretex-A9 with cache coherent memory hierarchy, and several application sub-systems. Each of these sub-systems are composed of highly optimized instruction processors, graphics/DSP processors, and custom hardware accelerators. Typically, these sub-systems utilize scratchpad memories (SPM) rather than support cache coherency. The overall architecture is an integration of the various sub-systems through a high bandwidth system-level interconnect (such as a Network-on-Chip (NoC)). The shift to MPSoCs has been fueled by three major factors: demand for high performance, the use of component libraries, and short design turn around time. As customers continue to desire more and more complex applications on their embedded devices the performance demand for these devices continues to increase. Designers have turned to using MPSoCs to address this demand. By using pre-made IP libraries designers can quickly piece together a MPSoC that will meet the application demands of the end user with minimal time spent designing new hardware. Additionally, the use of MPSoCs allows designers to generate new devices very quickly and thus reducing the time to market. In this work, a complete MPSoC synthesis design flow is presented. We first present a technique \cite{leary1_intro} to address the synthesis of the interconnect architecture (particularly Network-on-Chip (NoC)). We then address the synthesis of the memory architecture of a MPSoC sub-system \cite{leary2_intro}. Lastly, we present a co-synthesis technique to generate the functional and memory architectures simultaneously. The validity and quality of each synthesis technique is demonstrated through extensive experimentation.
ContributorsLeary, Glenn (Author) / Chatha, Karamvir S (Thesis advisor) / Vrudhula, Sarma (Committee member) / Shrivastava, Aviral (Committee member) / Beraha, Rudy (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Rapid technology scaling, the main driver of the power and performance improvements of computing solutions, has also rendered our computing systems extremely susceptible to transient errors called soft errors. Among the arsenal of techniques to protect computation from soft errors, Control Flow Checking (CFC) based techniques have gained a reputation

Rapid technology scaling, the main driver of the power and performance improvements of computing solutions, has also rendered our computing systems extremely susceptible to transient errors called soft errors. Among the arsenal of techniques to protect computation from soft errors, Control Flow Checking (CFC) based techniques have gained a reputation of effective, yet low-cost protection mechanism. The basic idea is that, there is a high probability that a soft-fault in program execution will eventually alter the control flow of the program. Therefore just by making sure that the control flow of the program is correct, significant protection can be achieved. More than a dozen techniques for CFC have been developed over the last several decades, ranging from hardware techniques, software techniques, and hardware-software hybrid techniques as well. Our analysis shows that existing CFC techniques are not only ineffective in protecting from soft errors, but cause additional power and performance overheads. For this analysis, we develop and validate a simulation based experimental setup to accurately and quantitatively estimate the architectural vulnerability of a program execution on a processor micro-architecture. We model the protection achieved by various state-of-the-art CFC techniques in this quantitative vulnerability estimation setup, and find out that software only CFC protection schemes (CFCSS, CFCSS+NA, CEDA) increase system vulnerability by 18% to 21% with 17% to 38% performance overhead. Hybrid CFC protection (CFEDC) increases vulnerability by 5%, while the vulnerability remains almost the same for hardware only CFC protection (CFCET); notwithstanding the hardware overheads of design cost, area, and power incurred in the hardware modifications required for their implementations.
ContributorsRhisheekesan, Abhishek (Author) / Shrivastava, Aviral (Thesis advisor) / Colbourn, Charles Joseph (Committee member) / Wu, Carole-Jean (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Memories play an integral role in today's advanced ICs. Technology scaling has enabled high density designs at the price paid for impact due to variability and reliability. It is imperative to have accurate methods to measure and extract the variability in the SRAM cell to produce accurate reliability projections for

Memories play an integral role in today's advanced ICs. Technology scaling has enabled high density designs at the price paid for impact due to variability and reliability. It is imperative to have accurate methods to measure and extract the variability in the SRAM cell to produce accurate reliability projections for future technologies. This work presents a novel test measurement and extraction technique which is non-invasive to the actual operation of the SRAM memory array. The salient features of this work include i) A single ended SRAM test structure with no disturbance to SRAM operations ii) a convenient test procedure that only requires quasi-static control of external voltages iii) non-iterative method that extracts the VTH variation of each transistor from eight independent switch point measurements. With the present day technology scaling, in addition to the variability with the process, there is also the impact of other aging mechanisms which become dominant. The various aging mechanisms like Negative Bias Temperature Instability (NBTI), Channel Hot Carrier (CHC) and Time Dependent Dielectric Breakdown (TDDB) are critical in the present day nano-scale technology nodes. In this work, we focus on the impact of NBTI due to aging in the SRAM cell and have used Trapping/De-Trapping theory based log(t) model to explain the shift in threshold voltage VTH. The aging section focuses on the following i) Impact of Statistical aging in PMOS device due to NBTI dominates the temporal shift of SRAM cell ii) Besides static variations , shifting in VTH demands increased guard-banding margins in design stage iii) Aging statistics remain constant during the shift, presenting a secondary effect in aging prediction. iv) We have investigated to see if the aging mechanism can be used as a compensation technique to reduce mismatch due to process variations. Finally, the entire test setup has been tested in SPICE and also validated with silicon and the results are presented. The method also facilitates the study of design metrics such as static, read and write noise margins and also the data retention voltage and thus help designers to improve the cell stability of SRAM.
ContributorsRavi, Venkatesa (Author) / Cao, Yu (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Clark, Lawrence (Committee member) / Arizona State University (Publisher)
Created2013
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Description
We are expecting hundreds of cores per chip in the near future. However, scaling the memory architecture in manycore architectures becomes a major challenge. Cache coherence provides a single image of memory at any time in execution to all the cores, yet coherent cache architectures are believed will not scale

We are expecting hundreds of cores per chip in the near future. However, scaling the memory architecture in manycore architectures becomes a major challenge. Cache coherence provides a single image of memory at any time in execution to all the cores, yet coherent cache architectures are believed will not scale to hundreds and thousands of cores. In addition, caches and coherence logic already take 20-50% of the total power consumption of the processor and 30-60% of die area. Therefore, a more scalable architecture is needed for manycore architectures. Software Managed Manycore (SMM) architectures emerge as a solution. They have scalable memory design in which each core has direct access to only its local scratchpad memory, and any data transfers to/from other memories must be done explicitly in the application using Direct Memory Access (DMA) commands. Lack of automatic memory management in the hardware makes such architectures extremely power-efficient, but they also become difficult to program. If the code/data of the task mapped onto a core cannot fit in the local scratchpad memory, then DMA calls must be added to bring in the code/data before it is required, and it may need to be evicted after its use. However, doing this adds a lot of complexity to the programmer's job. Now programmers must worry about data management, on top of worrying about the functional correctness of the program - which is already quite complex. This dissertation presents a comprehensive compiler and runtime integration to automatically manage the code and data of each task in the limited local memory of the core. We firstly developed a Complete Circular Stack Management. It manages stack frames between the local memory and the main memory, and addresses the stack pointer problem as well. Though it works, we found we could further optimize the management for most cases. Thus a Smart Stack Data Management (SSDM) is provided. In this work, we formulate the stack data management problem and propose a greedy algorithm for the same. Later on, we propose a general cost estimation algorithm, based on which CMSM heuristic for code mapping problem is developed. Finally, heap data is dynamic in nature and therefore it is hard to manage it. We provide two schemes to manage unlimited amount of heap data in constant sized region in the local memory. In addition to those separate schemes for different kinds of data, we also provide a memory partition methodology.
ContributorsBai, Ke (Author) / Shrivastava, Aviral (Thesis advisor) / Chatha, Karamvir (Committee member) / Xue, Guoliang (Committee member) / Chakrabarti, Chaitali (Committee member) / Arizona State University (Publisher)
Created2014
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Description
ABSTRACT The D flip flop acts as a sequencing element while designing any pipelined system. Radiation Hardening by Design (RHBD) allows hardened circuits to be fabricated on commercially available CMOS manufacturing process. Recently, single event transients (SET's) have become as important as single event upset (SEU) in radiation hardened high

ABSTRACT The D flip flop acts as a sequencing element while designing any pipelined system. Radiation Hardening by Design (RHBD) allows hardened circuits to be fabricated on commercially available CMOS manufacturing process. Recently, single event transients (SET's) have become as important as single event upset (SEU) in radiation hardened high speed digital designs. A novel temporal pulse based RHBD flip-flop design is presented. Temporally delayed pulses produced by a radiation hardened pulse generator design samples the data in three redundant pulse latches. The proposed RHBD flip-flop has been statistically designed and fabricated on 90 nm TSMC LP process. Detailed simulations of the flip-flop operation in both normal and radiation environments are presented. Spatial separation of critical nodes for the physical design of the flip-flop is carried out for mitigating multi-node charge collection upsets. The proposed flip-flop is also used in commercial CAD flows for high performance chip designs. The proposed flip-flop is used in the design and auto-place-route (APR) of an advanced encryption system and the metrics analyzed.
ContributorsKumar, Sushil (Author) / Clark, Lawrence (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Ogras, Umit Y. (Committee member) / Arizona State University (Publisher)
Created2014
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Description
In this thesis we deal with the problem of temporal logic robustness estimation. We present a dynamic programming algorithm for the robust estimation problem of Metric Temporal Logic (MTL) formulas regarding a finite trace of time stated sequence. This algorithm not only tests if the MTL specification is satisfied by

In this thesis we deal with the problem of temporal logic robustness estimation. We present a dynamic programming algorithm for the robust estimation problem of Metric Temporal Logic (MTL) formulas regarding a finite trace of time stated sequence. This algorithm not only tests if the MTL specification is satisfied by the given input which is a finite system trajectory, but also quantifies to what extend does the sequence satisfies or violates the MTL specification. The implementation of the algorithm is the DP-TALIRO toolbox for MATLAB. Currently it is used as the temporal logic robust computing engine of S-TALIRO which is a tool for MATLAB searching for trajectories of minimal robustness in Simulink/ Stateflow. DP-TALIRO is expected to have near linear running time and constant memory requirement depending on the structure of the MTL formula. DP-TALIRO toolbox also integrates new features not supported in its ancestor FW-TALIRO such as parameter replacement, most related iteration and most related predicate. A derivative of DP-TALIRO which is DP-T-TALIRO is also addressed in this thesis which applies dynamic programming algorithm for time robustness computation. We test the running time of DP-TALIRO and compare it with FW-TALIRO. Finally, we present an application where DP-TALIRO is used as the robustness computation core of S-TALIRO for a parameter estimation problem.
ContributorsYang, Hengyi (Author) / Fainekos, Georgios (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Software has a great impact on the energy efficiency of any computing system--it can manage the components of a system efficiently or inefficiently. The impact of software is amplified in the context of a wearable computing system used for activity recognition. The design space this platform opens up is immense

Software has a great impact on the energy efficiency of any computing system--it can manage the components of a system efficiently or inefficiently. The impact of software is amplified in the context of a wearable computing system used for activity recognition. The design space this platform opens up is immense and encompasses sensors, feature calculations, activity classification algorithms, sleep schedules, and transmission protocols. Design choices in each of these areas impact energy use, overall accuracy, and usefulness of the system. This thesis explores methods software can influence the trade-off between energy consumption and system accuracy. In general the more energy a system consumes the more accurate will be. We explore how finding the transitions between human activities is able to reduce the energy consumption of such systems without reducing much accuracy. We introduce the Log-likelihood Ratio Test as a method to detect transitions, and explore how choices of sensor, feature calculations, and parameters concerning time segmentation affect the accuracy of this method. We discovered an approximate 5X increase in energy efficiency could be achieved with only a 5% decrease in accuracy. We also address how a system's sleep mode, in which the processor enters a low-power state and sensors are turned off, affects a wearable computing platform that does activity recognition. We discuss the energy trade-offs in each stage of the activity recognition process. We find that careful analysis of these parameters can result in great increases in energy efficiency if small compromises in overall accuracy can be tolerated. We call this the ``Great Compromise.'' We found a 6X increase in efficiency with a 7% decrease in accuracy. We then consider how wireless transmission of data affects the overall energy efficiency of a wearable computing platform. We find that design decisions such as feature calculations and grouping size have a great impact on the energy consumption of the system because of the amount of data that is stored and transmitted. For example, storing and transmitting vector-based features such as FFT or DCT do not compress the signal and would use more energy than storing and transmitting the raw signal. The effect of grouping size on energy consumption depends on the feature. For scalar features energy consumption is proportional in the inverse of grouping size, so it's reduced as grouping size goes up. For features that depend on the grouping size, such as FFT, energy increases with the logarithm of grouping size, so energy consumption increases slowly as grouping size increases. We find that compressing data through activity classification and transition detection significantly reduces energy consumption and that the energy consumed for the classification overhead is negligible compared to the energy savings from data compression. We provide mathematical models of energy usage and data generation, and test our ideas using a mobile computing platform, the Texas Instruments Chronos watch.
ContributorsBoyd, Jeffrey Michael (Author) / Sundaram, Hari (Thesis advisor) / Li, Baoxin (Thesis advisor) / Shrivastava, Aviral (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Coarse-Grained Reconfigurable Architectures (CGRA) are a promising fabric for improving the performance and power-efficiency of computing devices. CGRAs are composed of components that are well-optimized to execute loops and rotating register file is an example of such a component present in CGRAs. Due to the rotating nature of register indexes

Coarse-Grained Reconfigurable Architectures (CGRA) are a promising fabric for improving the performance and power-efficiency of computing devices. CGRAs are composed of components that are well-optimized to execute loops and rotating register file is an example of such a component present in CGRAs. Due to the rotating nature of register indexes in rotating register file, it is very challenging, if at all possible, to hold and properly index memory addresses (pointers) and static values. In this Thesis, different structures for CGRA register files are investigated. Those structures are experimentally compared in terms of performance of mapped applications, design frequency, and area. It is shown that a register file that can logically be partitioned into rotating and non-rotating regions is an excellent choice because it imposes the minimum restriction on underlying CGRA mapping algorithm while resulting in efficient resource utilization.
ContributorsSaluja, Dipal (Author) / Shrivastava, Aviral (Thesis advisor) / Lee, Yann-Hang (Committee member) / Wu, Carole-Jean (Committee member) / Arizona State University (Publisher)
Created2014
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Description
This work describes the development of automated flows to generate pad rings, mixed signal power grids, and mega cells in a multi-project test chip. There were three major design flows that were created to create the test chip. The first was the pad ring which was used as the staring

This work describes the development of automated flows to generate pad rings, mixed signal power grids, and mega cells in a multi-project test chip. There were three major design flows that were created to create the test chip. The first was the pad ring which was used as the staring block for creating the test chip. This flow put all of the signals for the chip in the order that was wanted along the outside of the die along with creation of the power ring that is used to supply the chip with a robust power source.

The second flow that was created was used to put together a flash block that is based off of a XILIX XCFXXP. This flow was somewhat similar to how the pad ring flow worked except that optimizations and a clock tree was added into the flow. There was a couple of design redoes due to timing and orientation constraints.

Finally, the last flow that was created was the top level flow which is where all of the components are combined together to create a finished test chip ready for fabrication. The main components that were used were the finished flash block, HERMES, test structures, and a clock instance along with the pad ring flow for the creation of the pad ring and power ring.

Also discussed is some work that was done on a previous multi-project test chip. The work that was done was the creation of power gaters that were used like switches to turn the power on and off for some flash modules. To control the power gaters the functionality change of some pad drivers was done so that they output a higher voltage than what is seen in the core of the chip.
ContributorsLieb, Christopher (Author) / Clark, Lawrence (Thesis advisor) / Holbert, Keith E. (Committee member) / Seo, Jae-Sun (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Stream processing has emerged as an important model of computation especially in the context of multimedia and communication sub-systems of embedded System-on-Chip (SoC) architectures. The dataflow nature of streaming applications allows them to be most naturally expressed as a set of kernels iteratively operating on continuous streams of data. The

Stream processing has emerged as an important model of computation especially in the context of multimedia and communication sub-systems of embedded System-on-Chip (SoC) architectures. The dataflow nature of streaming applications allows them to be most naturally expressed as a set of kernels iteratively operating on continuous streams of data. The kernels are computationally intensive and are mainly characterized by real-time constraints that demand high throughput and data bandwidth with limited global data reuse. Conventional architectures fail to meet these demands due to their poorly matched execution models and the overheads associated with instruction and data movements.

This work presents StreamWorks, a multi-core embedded architecture for energy-efficient stream computing. The basic processing element in the StreamWorks architecture is the StreamEngine (SE) which is responsible for iteratively executing a stream kernel. SE introduces an instruction locking mechanism that exploits the iterative nature of the kernels and enables fine-grain instruction reuse. Each instruction in a SE is locked to a Reservation Station (RS) and revitalizes itself after execution; thus never retiring from the RS. The entire kernel is hosted in RS Banks (RSBs) close to functional units for energy-efficient instruction delivery. The dataflow semantics of stream kernels are captured by a context-aware dataflow execution mode that efficiently exploits the Instruction Level Parallelism (ILP) and Data-level parallelism (DLP) within stream kernels.

Multiple SEs are grouped together to form a StreamCluster (SC) that communicate via a local interconnect. A novel software FIFO virtualization technique with split-join functionality is proposed for efficient and scalable stream communication across SEs. The proposed communication mechanism exploits the Task-level parallelism (TLP) of the stream application. The performance and scalability of the communication mechanism is evaluated against the existing data movement schemes for scratchpad based multi-core architectures. Further, overlay schemes and architectural support are proposed that allow hosting any number of kernels on the StreamWorks architecture. The proposed oevrlay schemes for code management supports kernel(context) switching for the most common use cases and can be adapted for any multi-core architecture that use software managed local memories.

The performance and energy-efficiency of the StreamWorks architecture is evaluated for stream kernel and application benchmarks by implementing the architecture in 45nm TSMC and comparison with a low power RISC core and a contemporary accelerator.
ContributorsPanda, Amrit (Author) / Chatha, Karam S. (Thesis advisor) / Wu, Carole-Jean (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Shrivastava, Aviral (Committee member) / Arizona State University (Publisher)
Created2014