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This chapter is intended for readers who do not have a background in bone biomechanics. It gives a description of bone, highlighting its complex and hierarchical structure, starting at the macroscopic scale from an entire bone, such as the femur, down to the nanoscopic scale and its basic components: the collagen fibers and the mineral crystals. Then, some definitions and concepts of biomechanics are given in relation to the hierarchical structure of bone. The goal is to define the main parameters that can be used to assess bone mechanical competence. Some mechanical features are accessible using the quantitative ultrasound (QUS) technologies that are presented in subsequent chapters. Finally, the clinical context in which QUS has been developed is described. Diagnosis and follow-up of osteoporosis is a major public health problem in which QUS can play a role. [ABSTRACT FROM AUTHOR]

Avoiding message dependent deadlocks in communication fabrics is critical for modern microarchitectures. If discovered late in the design cycle, deadlocks lead to missed project deadlines and suboptimal design decisions. One approach to avoid this problem is to get high level of confidence on an early microarchitectural model. However, formal proofs of liveness even on abstract models are hard due to large number of queues and distributed control. In this work we address liveness verification of communication fabrics described in the form of high-level microarchitectural models which use a small set of well-defined primitives. We prove that under certain realistic restrictions, deadlock freedom can be reduced to unsatisfiability of a system of Boolean equations. Using this approach, we have automatically verified liveness of several non-trivial models (derived from industrial microarchitectures), where state-of-the-art model checkers failed and pen and paper proofs were either tedious or unknown. [ABSTRACT FROM AUTHOR]

Indirect branch prediction is a performance limiting factor for current computer systems, preventing superscalar processors from exploiting the available ILP. Indirect branches are responsible for 55.7% of mispredictions in our benchmark set, although they only stand for 15.5% of dynamic branches. Moreover, a 10.8% average IPC speedup is achievable by perfectly predicting all indirect branches. The Multi-Stage Cascaded Predictor (MSCP) is a mechanism proposed for improving indirect branch prediction. In this paper, we show that a MSCP can replace a BTB and accurately predict the target address of both indirect and non-indirect branches. We do a detailed analysis of MSCP behavior and evaluate it in a realistic setup, showing that a 5.7% average IPC speedup is achievable. [ABSTRACT FROM AUTHOR]