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Over the last decade the relative latency of access to shared memory by multicore increased as wire resistance dominated latency and low wire density layout pushed multi-port memories farther away from their ports. Various techniques were deployed to improve average memory access latencies, such as speculative pre-fetching and branch-prediction, often leading to high variance in execution time which is unacceptable in real-time systems. Smart DMAs can be used


High-Throughput JPEG2000 (HTJ2K) is a new addition to the JPEG2000 suite of coding tools; it has been recently approved as Part-15 of the JPEG2000 standard, and the JPH file extension has been designated for it. The HTJ2K employs a new “fast” block coder that can achieve higher encoding and decoding throughput than a conventional JPEG2000 (C-J2K) encoder. The higher throughput is achieved because the HTJ2K codec processes wavelet coefficients in a smaller number of steps than C-J2K.


Sparse code multiple access (SCMA) uses multi-dimensional sparse codewords to transmit user data. The expectation propagation algorithm (EPA) exploiting the sparse property shows linear complexity growth and thus is preferred for multi-user detection. To further reduce the complexity, a convergence-aware based EPA for uplink MIMO SCMA systems is proposed. Techniques including user termination, antenna termination, and codebook reduction are adopted. The user termination must be combined with the iteration constraint to avoid misjudgement.


High-throughput JPEG2000 (HTJ2K), also known as JPEG 2000 Part 15, is the most recent addition to the JPEG2000 suite of coding tools. The file extension JPH has been designated for compressed images employing this new part of the standard. This new part describes a “fast” block coder for the JPEG 2000 format, while retaining most other JPEG2000 features and capabilities intact.


The conversion of an algorithm to fixed-point arithmetic is commonly achieved with a large and fixed-number of simulations. Nevertheless, when simulating a fixed and ar- bitrary large number of samples, no confidence information is given on the characterization, and this method is often time-inefficient. To overcome this limitation, we propose a new method for noise evaluation. The error induced by fixed-point coding is statistically characterized to compute the noise power with an adaptive and reduced number of simulations.


Inertial navigation allows tracking and updating the position and orientation of a moving object based on accelerometer and gyroscope data without external positioning aid, such as GPS. Therefore, inertial navigation is an essential technique for, e.g., indoor positioning. As inertial navigation is based on integration of acceleration vector components, computation errors accumulate and make the position and orientation estimate drift.