IEEE transactions on computer-aided design of integrated circuits and systems : a publication of the IEEE Circuits and Systems Society

DRAM memory is a major resource shared among cores in a chip multiprocessor (CMP) system. Memory requests from different threads can interfere with each other. Existing memory access scheduling techniques try to optimize the overall data throughput obtained from the DRAM and thus do not take into account inter-thread interference. Therefore, different threads running together on the same chip can ex- perience extremely different memory system performance: one thread can experience a severe slowdown or starvation while another is un- fairly prioritized by the memory scheduler. This paper proposes a new memory access scheduler, called the Stall-Time Fair Memory scheduler (STFM), that provides quality of service to different threads sharing the DRAM memory system. The goal of the proposed scheduler is to "equalize" the DRAM-related slowdown experienced by each thread due to interference from other threads, without hurting overall system performance. As such, STFM takes into account inherent memory characteristics of each thread and does not unfairly penalize threads that use the DRAM system without interfering with other threads. We show that STFM significantly reduces the unfairness in the DRAM system while also improving system throughput (i.e., weighted speedup of threads) on a wide variety of workloads and systems. For example, averaged over 32 different workloads running on an 8-core CMP, the ratio between the highest DRAM-related slowdown and the lowest DRAM-related slowdown reduces from 5.26X to 1.4X, while the average system throughput improves by 7.6%. We qualitatively and quantitatively compare STFM to one new and three previously- proposed memory access scheduling algorithms, including network fair queueing. Our results show that STFM provides the best fairness, system throughput, and scalability.

/pdf/stall-time-fair-memory-access-scheduling-for-chip-kj13rlydtp.pdf

Stall-Time Fair Memory Access Scheduling for Chip Multiprocessors

Process variations will greatly impact the stability, leakage power consumption, and performance of future microprocessors. These variations are especially detrimental to 6T SRAM (6-transistor static memory) structures and will become critical with continued technology scaling. In this paper, we propose new on-chip memory architectures based on novel 3T1D DRAM (3-transistor, 1-diode dynamic memory) cells. We provide a detailed comparison between 6T and 3T1D designs in the context of a L1 data cache. The effects of physical device variation on a 3T1D cache can be lumped into variation of data retention times. This paper proposes a range of cache refresh and placement schemes that are sensitive to reten- tion time, and we show that most of the retention time variations can be masked by the microarchitecture when using these schemes. We have performed detailed circuit and architectural simulations assuming different degrees of variability in advanced technology nodes, and we show that the resulting memory architecture can tol- erate large process variations with little or even no impact on per- formance when compared to ideal 6T SRAM designs. Furthermore, these designs are robust to memory cell stability issues and can achieve large power savings. These advantages make the new mem- ory architectures a promising choice for on-chip variation-tolerant cache structures required for next generation microprocessors.

/pdf/process-variation-tolerant-3t1d-based-cache-architectures-45zv4uryey.pdf

Process Variation Tolerant 3T1D-Based Cache Architectures

Static-timing analysis (STA) has been one of the most pervasive and successful analysis engines in the design of digital circuits for the last 20 years. However, in recent years, the in- creased loss of predictability in semiconductor devices has raised concern over the ability of STA to effectively model statistical variations. This has resulted in extensive research in the so-called statistical STA (SSTA), which marks a significant departure from the traditional STA framework. In this paper, we review the recent developments in SSTA. We first discuss its underlying models and assumptions, then survey the major approaches, and close by discussing its remaining key challenges.

Keynote Paper Statistical Timing Analysis: From Basic Principles to State of the Art

Static-timing analysis (STA) has been one of the most pervasive and successful analysis engines in the design of digital circuits for the last 20 years. However, in recent years, the increased loss of predictability in semiconductor devices has raised concern over the ability of STA to effectively model statistical variations. This has resulted in extensive research in the so-called statistical STA (SSTA), which marks a significant departure from the traditional STA framework. In this paper, we review the recent developments in SSTA. We first discuss its underlying models and assumptions, then survey the major approaches, and close by discussing its remaining key challenges.

Statistical Timing Analysis: From Basic Principles to State of the Art

Process parameter variations are expected to be significantly high in a sub-50-nm technology regime, which can severely affect the yield, unless very conservative design techniques are employed. The parameter variations are random in nature and are expected to be more pronounced in minimum geometry transistors commonly used in memories such as SRAM. Consequently, a large number of cells in a memory are expected to be faulty due to variations in different process parameters. We analyze the impact of process variation on the different failure mechanisms in SRAM cells. We also propose a process-tolerant cache architecture suitable for high-performance memory. This technique dynamically detects and replaces faulty cells by dynamically resizing the cache. It surpasses all the contemporary fault tolerant schemes such as row/column redundancy and error-correcting code (ECC) in handling failures due to process variation. Experimental results on a 64-K direct map L1 cache show that the proposed technique can achieve 94% yield compared to its original 33% yield (standard cache) in a 45-nm predictive technology under /spl sigma//sub Vt-inter/=/spl sigma//sub Vt-intra/=30 mV.

http://online.sfsu.edu/mahmoodi/papers/paper_J6.pdf

A process-tolerant cache architecture for improved yield in nanoscale technologies

Independent control of front and back gate in double gate (DG) devices can be used to merge parallel transistors in noncritical paths. This reduces the effective switching capacitance and, hence, the dynamic power dissipation of a circuit. However, efficient design of large-scale circuits with DG devices is not well explored due to lack of proper modeling and large-scale design simulation tools. In this paper, we propose several low-power circuit options using independent gate FinFETs. We developed semianalytical models for different FinFET logic gates to predict their performance. An efficient circuit synthesis methodology comprised of proposed low-power logic options in FinFET design library has been developed. Results show about 8.5% area savings and 18% power savings over conventional FinFET technology for ISCAS85 benchmark circuits in 45-nm technology with no performance penalty.

http://online.sfsu.edu/mahmoodi/papers/paper_J14.pdf

Modeling and Circuit Synthesis for Independently Controlled Double Gate FinFET Devices

Designing high-performance systems with high yield under parameter variations has raised serious design challenges in nanometer technologies. In this paper, we propose a profit-aware yield model, based on which we present a statistical design methodology to improve profit of a design considering frequency binning and product price profile. A low-complexity sensitivity-based gate sizing algorithm is developed to improve the profitability of design over an initial yield-optimized design. We also propose an algorithm to determine optimal bin boundaries for maximizing profit with frequency binning. Finally, we present an integrated design methodology for simultaneous sizing and bin placement to enhance profit under an area constraint. Experiments on a set of ISCAS85 benchmarks show up to 26% (36%) improvement in profit for fixed bin (for simultaneous sizing and bin placement) with three frequency bins considering both leakage and delay bounds compared to a design optimized for 90% yield at iso-area.

Speed binning aware design methodology to improve profit under parameter variations

Operating frequency of a pipelined circuit is determined by the delay of the slowest pipeline stage. However, under statistical delay variation in sub-100nm technology regime, the slowest stage is not readily identifiable and the estimation of the pipeline yield with respect to a target delay is a challenging problem. We have proposed analytical models to estimate yield for a pipelined design based on delay distributions of individual pipe stages. Using the proposed models, we have shown that change in logic depth and imbalance between the stage delays can improve the yield of a pipeline. A statistical methodology has been developed to optimally design a pipeline circuit for enhancing yield. Optimization results show that, proper imbalance among the stage delays in a pipeline improves design yield by 9% for the same area and performance (and area reduction by about 8.4% under a yield constraint) over a balanced design.

Statistical Modeling of Pipeline Delay and Design of Pipeline under Process Variation to Enhance Yield in sub-100nm Technologies

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Animesh Datta

Papers

A process-tolerant cache architecture for improved yield in nanoscale technologies

Modeling and Circuit Synthesis for Independently Controlled Double Gate FinFET Devices

Speed binning aware design methodology to improve profit under parameter variations

Statistical Modeling of Pipeline Delay and Design of Pipeline under Process Variation to Enhance Yield in sub-100nm Technologies

Statistical Modeling of Pipeline Delay and Design of Pipeline under Process Variation to Enhance Yield in sub-100nm Technologies