Scheduling tests for VLSI systems under power constraints

We present a mathematical model for the problem of scheduling tests for core-based system-on-chip (SOC) VLSI designs. Given a set of tests for each core in the SOC and a set of test resources (e.g., test access mechanisms (TAM)), we determine the test plan for the application of the tests to the SOC. Test planning in this paper refers to the combined activities of test access architecture partitioning and test scheduling. These activities must be performed in conjunction as the choice of the test access architecture influences the test schedule. We justify the formulation of test scheduling w.r.t. minimum average completion time criterion as compared to minimum makespan. We show that then the problem of scheduling tests on TAMs can be mapped onto a graph theoretic problem which has a polynomial time optimal solution. We have implemented our algorithm as a test planner tool TPLAN. We present the theoretical analysis of our approach in this paper, and compare our results against those published earlier using integer linear programming techniques with encouraging results.

This paper presents an efficient method to determine minimum system-on-chip (SOC) test schedules with precedence and power constraints based on simulated annealing. The problem is solved using a partitioned testing scheme with run to completion that minimizes the number of idle test slots. The method can handle SOC test scheduling with and without power constraints in addition to precedence constraints that preserve desirable orderings among tests. We present experimental results for various SOC examples that demonstrate the effectiveness of the method. The method achieved optimal test schedules in all attempted cases in a short CPU time.

This paper presents a stage-based test scheduling for memory cores with BISR scheme under power constraint. We introduce a model to compute the expected test time for a given test schedule for memory cores with BISR scheme based on pass probabilities, and propose a test scheduling algorithm to minimize the expected test time. Experimental results show a significant expected test time reduction compared to the core-based test scheduling method which minimizes the test time.

This paper addresses the problem of priority assignment in multiprocessor real-time systems using global fixed task-priority pre-emptive scheduling. In this paper, we prove that Audsley’s Optimal Priority Assignment (OPA) algorithm, originally devised for uniprocessor scheduling, is applicable to the multiprocessor case, provided that three conditions hold with respect to the schedulability tests used. Our empirical investigations show that the combination of optimal priority assignment policy and a simple compatible schedulability test is highly effective, in terms of the number of tasksets deemed to be schedulable. We also examine the performance of heuristic priority assignment policies such as Deadline Monotonic, and an extension of the TkC priority assignment policy called DkC that can be used with any schedulability test. Here we find that Deadline Monotonic priority assignment has relatively poor performance in the multiprocessor case, while DkC priority assignment is highly effective.

In this paper, single- and multi- user Resource Allocation (RA) optimization problems considering transmit power and minimum rate constraint of Mobile Station (MS) for maximizing MS' energy efficiency, measured as bits-per-joule (bpj), are addressed. Assume channel state information of all MSs is known by base station. We propose uplink RA algorithms, performing subcarrier assignment and power allocation, for optimizing bpj of MS in a single-cell OFDMA-based cellular network for both single- and multi- user scenarios. In the single-user case, we propose RA algorithms, which utilize the closed-form solution derived by applying Lambert-W function and an iterative approach based on Karush---Kuhn---Tucker conditions respectively to achieve optimal bpj of MS. In the multi-user case, centralized iterative multi-user RA algorithms for maximizing sum of MS' bpj, performing joint subcarrier assignment and power allocation iteratively, are proposed by utilizing the proposed single-user RA schemes. In particular, tradeoffs between energy efficiency and spectral efficiency are fully investigated, and the influence of MS' power and minimum rate constraints on bpj performance is also studied. The effectiveness of proposed algorithms is presented by numerical experiments. Numerical results demonstrate the proposed algorithms can enhance bpj significantly with limited loss of total throughput compared to the sum-rate maximization algorithm (in Moretti et al., IEEE Trans Veh Technol 60(4):1788---1798, 2011).

This study will present an experimental evaluation of the variable-feedrate intelligent segmentation (VFIS) method described by Mayor and Sodemann (2008, “Intelligent Tool-Path Segmentation for Improved Stability and Reduced Machining Time in Micromilling,” ASME J. Manuf. Sci. Eng., 130(3), p. 031121). The apparatus for the tests will be identified and the approach to the testing procedure will be laid out, including the means of evaluation of the method. A detailed explanation is then given for the choice of process parameters. This is followed by the introduction of the β parameter as an additional factor in the VFIS implementation. Results are presented from cutting tests. The first set of test results presented is from a complete set of evaluation tests performed on sine wave geometries. The second set is an evaluation of the fan and airfoil shapes used previously in the numerical simulations of the VFIS method. It is found that the VFIS method is able to successfully constrain geometric error to within specified bounds in most cases. The cutting time for the VFIS method shows as much as 53% reduction relative to the nonuniform rational B-spline-based trajectory generation method.

The generalized multiframe task model (GMF) extends the sporadic task model and multiframe task model. Each frame in the GMF model contains an execution time, a relative deadline, and a minimum inter-arrival time. These parameters are fixed after task specification time in the GMF model. However, multimedia and adaptive control systems may be overloaded and no longer stabilized when the task parameters in such systems are not flexible. In order to address this problem, deadlines and periods of frames may change to alleviate temporal overload, e.g., in the parameter adaptation and elastic scheduling model. In this paper, we propose a new model GMF-PA (the GMF model with parameter adaptation). This model allows task parameters to be flexible in arbitrary-deadline systems. A necessary schedulability test based on mixed-integer linear programming is given to check the schedulability under EDF scheduling and optimally assign frame deadlines and periods at the same time. We also prove that the test is a sufficient and necessary schedulability test when frame deadlines and periods must be integers. An approximation algorithm is also deployed to reduce computational running time and indicates a sufficient schedulability test in general. The speed-up factor of our approximation algorithm is $$1+\epsilon $$ where $$\epsilon $$ can be arbitrarily small, with respect to the exact schedulability test of GMF-PA tasks under EDF. We also apply the GMF model to self-suspending tasks. By extending recent work on scheduling self-suspending tasks, we remove the assumption that frame deadlines are equally assigned in self-suspending tasks, and the system is extended from constrained-deadline systems to arbitrary-deadline systems. We have done extensive experiments to show that the schedulability ratio is improved using our techniques in our GMF-PA model.

Two numerical approaches, the Robust-Generalized Iterative Approach (R-GIA) and the Robust-Transmit Covariance Optimization Approach (R-TCOA), are proposed for jointly designing the minimum mean square error (MMSE) precoders and decoders of uplink multiuser multiple-input-multiple-output (MIMO) systems with arbitrary linear equality power constraints and possibly imperfect channel state information (CSI). The R-TCOA always gives optimum solutions but is only applicable when the rank constraints on the precoders are relaxed, the spatial correlation matrix for the transmit antennas of each user is an identity matrix, and there exists a scalar such that squaring the source covariance matrices is the same as multiplying them by it. The statistics of the CSI error also need to be the same for all users if the power constraints of the users are interdependent. The R-GIA, on the other hand, has no such restrictions. But whenever the R-TCOA is applicable, both approaches converge, and all the transmit covariance matrices are full rank, the two solutions are actually equivalent (i.e. the R-GIA is also optimum)! Numerical results show that these two robust approaches, for the most part, outperform their non-robust counterparts in various different channel correlation scenarios.

The generalized multiframe task model (GMF) extends the sporadic task model and multiframe task model. Each frame in the GMF model contains an execution time, a relative deadline, and a minimum inter-arrival time. These parameters are fixed after task specification time in the GMF model. However, multimedia and adaptive control systems may be overloaded and no longer stabilized when the task parameters in such systems are not flexible. In order to address this problem, deadlines and periods may change to alleviate temporal overload, for example in the parameter adaption and elastic scheduling model. In this paper, we propose a new model GMF-PA (the GMF model with parameter adaption). This model allows task parameters to be flexible in arbitrary-deadline systems. A necessary schedulability test based on mixed-integer linear programming (MILP) is given to check the schedulability under EDF scheduling and optimally assign deadlines and periods at the same time. We also prove that the test is a sufficient and necessary schedulability test when task parameters must be integers. An approximation algorithm is also deployed to reduce computational running time. The speed-up factor of our approximation algorithm is 1+a#x0395; where a#x0395; can be arbitrarily small, with respect to the exact schedulability test of GMF-PA tasks under EDF. We also apply the GMF model to self-suspending tasks. By extending recent work on scheduling self-suspending tasks, we remove the assumption that deadlines are equally assigned in self-suspending tasks, and the system is extended from constrained-deadline systems to arbitrary-deadline systems. We have done exhaustive experiments to show that the schedulability ratio is improved using our techniques in our GMF-PA model.

Overheating has been acknowledged as a major issue in testing complex SOCs. Several power constrained system-level DFT solutions (power constrained test scheduling) have recently been proposed to tackle this problem. However, as it will be shown in this paper, imposing a chip-level maximum power constraint doesn't necessarily avoid local overheating due to the non-uniform distribution of power across the chip. This paper proposes a new approach for dealing with overheating during test, by embedding thermal awareness into test scheduling. The proposed approach facilitates rapid generation of thermal-safer test schedules without requiring time-consuming thermal simulations. This is achieved by employing a low-complexity test session thermal model used to guide the test schedule generation algorithm. This approach reduces the chances of a design re-spin due to potential overheating during test.

Based on the concept of optimal signal subspace, signal spectrum transformation is carried out according to channel state information before transmission, and system performance can be improved considerably. In this paper, we propose an adaptive modulation algorithm that guarantees a desired bit error rate with uniform power allocation, and the algorithm has low complexity and high spectrum efficiency. Our approach is novel in that we optimize both bit allocation and power allocation to maximize spectral efficiency under the constraint of power and bit error rate. The new adaptive modulation algorithm can greatly improve system performance without increasing system complexity significantly. (4 pages)

Robots are complex electromechanical systems which often exhibit rapid, unpredictable, and potentially dangerous behavior in the presence of faults. In this paper, we present a novel quantum-inspired approach to fault detection within robot systems. The approach is based on a new fault detection model termed Quantum Analytical Redundancy (QAR) within a Fault Tree framework. The QAR method evolves quantum states with the ability to represent the internal dependencies of data within a provably complete set of fault detection tests. Our research centers on simulation of the approach, with testing and evaluation planned on rigid-link robot manipulator hardware.

Overhead conductors are prone to wind-induced vibrations which further influence transmission line infrastructures. Cascading failures of transmission lines may lead to major power outage. Several analytical and experimental techniques have been evolved across the world in order to nullify the conductors' vibrations. In this experimental work, the ACSR Zebra conductor has been used for power transmission. This paper presents hexa spacer damper for dissipation of vibration energy of 765 kV transmission lines. Exclusively designed and developed damper has been validated based on the field test findings at Hydro Québec Test Station, Canada. These bundled conductors are particularly susceptible to wind-induced vibrations in the recurrence scope of 10-60 Hz because of vortex shedding. A complete set of the field tests have been conducted while installing 27 numbers of hexa spacer dampers at different sub-span lengths across the test line. The aim of this test is to assess the damping property of hexa spacer damper by precise measurement with the help of sensor embedded on the actual model and vibration emulated mechanism for Aeolian vibrations and sub-range motions. The test findings confirm effectiveness of the in-house developed hexa spacer damper.

Calcium (Ca) represents about 40% of the total mineral mass, mainly in the bone, providing mechanical strength to the skeleton and teeth. An adequate Ca intake is necessary for bone growth and development in children and adolescents and for maintaining bone mineral loss in elderly age. Ca deficiency predisposes to osteopenia and osteoporosis. Healthy nutrition, including an adequate intake of Ca-rich food, is paramount to prevent and cure osteoporosis. Recently, several clinical studies have demonstrated that, in conditions of Ca dysmetabolism, Ca-rich mineral water is beneficial as a valuable source of Ca to be used as an alternative to caloric Ca-rich dairy products. Although promising, these data have been collected from small groups of participants. Moreover, they mainly regard the effect of Ca-rich mineral water on bone metabolism. In contrast, an investigation of the effect of Ca supplementation on systemic metabolism is needed to address the spreading of systemic metabolic dysfunction often associated with Ca dysmetabolism. In the present study, we analyzed urine and blood sera of 120 women in perimenopausal condition who were subjected for six months to 2l daily consumption of bicarbonate–calcium mineral water marketed under ®Lete. Remarkably, this water, in addition to being rich in calcium and bicarbonate, is also low in sodium. A complete set of laboratory tests was carried out to investigate whether the specific water composition was such to confirm the known therapeutic effects on bone metabolism. Second, but not least, urine and blood sera were analyzed using NMR-based metabolomic procedures to investigate, other than the action on Ca metabolism, potential system-wide metabolic effects. Our data show that Lete water is a valid supplement for compensating for Ca dysmetabolism and preserving bone health and integrity.

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