A novel slave clock-gating technique in [5] is designed to save power when the master and slave latches of a low-power flip-flop reach certain correlated states (e.g., both latches are at logic 0 or 1). Testing this clock-gating circuit is essential for power-sensitive applications, but is also very challenging. This is because power consumption increase is its only defective behavior, and it involves cell internal states, both of which are unfriendly to general automatic test-pattern generation (ATPG). This paper proposes an innovative method to test the slave clock-gating circuitry structurally with slight modification of the flop cell. The implementation on a two-latch version of a level-sensitive scan design (LSSD) flip-flop and its capability of extending to other types of flip-flop cells are presented.

There is an ever-increasing demand for higher performance microprocessors within a given power budget. This demand forces design choices - that were once seen only in high-speed custom blocks - to spread throughout the microprocessor core. These unique design structures, combined with the nanometer technology test challenges such as crosstalk, process variations, power-supply noise, and resistive short and open defects, lead to unique test challenges for today's high-performance microprocessor core. In this paper, we present the scan architecture-related design-for-test (DFT) features and corresponding verification strategies of the nextgeneration Advanced Micro Devices (AMD) high-performance microprocessor core.

This paper describes TANOR, an automated framework for designing hardware accelerators for numerical computation on reconfigurable platforms. Applications utilizing numerical algorithms on large-size data sets require high-throughput computation platforms. The focus is on N-body interaction problems which have a wide range of applications spanning from astrophysics to molecular dynamics. The TANOR design flow starts with a MATLAB description of a particular interaction function, its parameters, and certain architectural constraints specified through a graphical user interface. Subsequently, TANOR automatically generates a configuration bitstream for a target FPGA along with associated drivers and control software necessary to direct the application from a host PC. Architectural exploration is facilitated through support for fully custom fixed-point and floating-point representations in addition to standard number representations such as single-precision floating point. Moreover, TANOR enables joint exploration of algorithmic and architectural variations in realizing efficient hardware accelerators. TANOR's capabilities have been demonstrated for three different N-body interaction applications: the calculation of gravitational potential in astrophysics, the diffusion or convolution with Gaussian kernel common in image processing applications, and the force calculation with vector-valued kernel function in molecular dynamics simulation. Experimental results show that TANOR-generated hardware accelerators achieve lower resource utilization without compromising numerical accuracy, in comparison to other existing custom accelerators.

This paper presents accurate area and power estimation models for implementations using FPGAs from the Xilinx Virtex-2Pro family. These models are designed to facilitate efficient design space exploration in an automated algorithm-architecture codesign framework. Detailed models for accurately estimating the number of slices, block RAMs and 18times18-bit multipliers for fixed point and floating-point IP cores have been developed. These models are also utilized to develop accurate power models that consider the effect of logic power, signal power, clock power and I/O power. In all cases, the model coefficients have been derived by using curve fitting or regression analysis. The modeling error for the IP cores is very small (average 0.95%). The error for fairly large examples such as floating point implementation of 8-point FFTs is also quite small; it is 1.87% for estimation of number of slices and 3.48% for estimation of power consumption.

Algorithm-architecture co-exploration is hindered by the lack of efficient tools. As a consequence, designers are currently able to explore only a limited set of points in the whole design space. Therefore, a tool that can allow fast exploration of algorithmic and architectural tradeoffs in an automated manner is highly desired. In this paper, we describe TANOR an automated tool targeted for designing hardware accelerators for the class of N-body interaction problems. The design flow, starting from a high level (MATLAB) description, configures the entire system automatically. We describe the design of TANOR and demonstrate the effectiveness and adaptability of our tool using three different target applications, namely, the gravitational kernel used in astrophysics, the gaussian kernel common in image processing applications, and a force calculation kernel applied in molecular dynamics. Our results demonstrate that TANOR generates hardware accelerator that are competitive with existing custom accelerator.