Abstract: This paper presents a new SIMD technique to implement efficiently on a DSP a parallel Max-Log-MAP algorithm for turbo decoders. It consists in using SIMD instructions to perform several independent trellises in parallel. This trellis parallelization is made possible by the use

. At the same time, a number of microprocessor architectures have emerged which have VLIW and SIMD structures that are well matched to the needs of the ILP compilers. Most of these processors are targeted at embedded applications such as multimedia and communications, rather than general-purpose systems

Thesis: “Overview and comparison of Hardware and Software SIMD techniques in VLIW archi-tectures”

solution is to use sample-point density estimation instead of k-nearest neighbor density estimation, a technique drawn from reverse photon mapping. Sample-point estimation removes the overheads that make SIMD instructions impractical, while retaining the same benefits and image quality as traditional

. We present compilation techniques for Simple Maude, a declarative programming language based on Rewriting Logic which supports term, graph, and object-oriented rewriting. We show how to compile various constructs of Simple Maude onto SIMD and MIMD/SIMD massively parallel architectures

and Halevi, but their key generation method appears to exclude the SIMD style operation alluded to by Smart and Vercauteren. In this paper, we show how to select parameters to enable such SIMD operations, whilst still maintaining practicality of the key generation technique of Gentry and Halevi. As such, we

shape distributions using stochastic optimization techniques (i.e. simulated annealing). Online, matching involves a simultaneous coarse-to-fine approach over the shape hierarchy and over the transformation parameters. Very large speedup factors are typically obtained when comparing this approach

The three generations of postings list compression strategies (Var-iable Byte Encoding, Word Aligned Codes, and SIMD Codecs) are examined in order to test whether or not each truly represented a generational change – they do. Some weaknesses of the current SIMD-based schemes are identified and a

Instruction Word (VLIW) architectures have multiple functional units to take advantage of vastly available Instruction Level Parallelism (ILP) in such applications. Single Instruction Multiple Data (SIMD) techniques operate on multiple data in a single instruction (exploiting data parallelism). This paper

. Additionally, we show that the hardware overhead of dynamic optimization is mod-est, hardware changes do not affect cycle time of the pro-cessor, and the performance impact of abstracting the SIMD accelerator is negligible. We conclude that using dynamic techniques to map instructions onto SIMD accelerators