Global ETD Search

Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.

Results

Showing 1 to 13 of 13 for “"Single instruction, multiple data (SIMD)"”.

  1. VeGen: A Vectorizer Generator for SIMD and Beyond

    Vector instructions are ubiquitous in modern processors. Traditional compiler auto-vectorization techniques have focused on targeting single instruction multiple data (SIMD) instructions. However, these auto-vectorization techniques are not sufficiently powerful to model non-SIMD vector …

    mit Repository record for VeGen: A Vectorizer Generator for SIMD and Beyond (opens in a new tab)

  2. Polyhedral Code Transformation for Julia

    … (CPU) code performance is highly dependent on instruction and data parallelism. Instruction parallelism is largely focused on CPU cores and threading, while data parallelism relies on specialized vectors. Single-instruction, multiple-data (SIMD) vectors allow for a single instruction to be …

    mit Repository record for Polyhedral Code Transformation for Julia (opens in a new tab)

  3. Computing the fast Fourier transform on SIMD microprocessors

    … (FFT) of a power-of-two length signal on single-instruction, multiple-data (SIMD) microprocessors faster than or very close to the speed of state of the art libraries such as FFTW (“Fastest Fourier Transform in the West”), SPIRAL and Intel Integrated Performance Primitives (IPP). The …

    waikato-masters Repository record for Computing the fast Fourier transform on SIMD microprocessors (opens in a new tab)

  4. Scalable trap technology for quantum computing with ions

    … a trapped atomic ion. Physics experiments with single atomic ions acting as "quantum bits" have demonstrated many of the ingredients for a quantum computer. But to perform useful computations these experimental systems will need to be vastly scaled-up. Our goal is to engineer systems for …

    mit Repository record for Scalable trap technology for quantum computing with ions (opens in a new tab)

  5. Accelerated Adjoint Algorithmic Differentiation with Applications in Finance

    … on all three dimensions implemented by the GPU: Instruction Level Parallelism (ILP), Thread level parallelism (TLP), and Single Instruction Multiple Data (SIMD). We estimate the forward pass of the Milstein discretisation contains an ILP of 3.57 which is between the average range of 2-4. Monte …

    cape-town Repository record for Accelerated Adjoint Algorithmic Differentiation with Applications in Finance (opens in a new tab)

  6. Enhancing Portability in High Performance Computing: Designing Fast Scientific Code with Longevity

    … point solver requiring a high degree of data transfer bandwidth of a type commonly used in high performance applications used for computing a solution to partial differential equations (PDEs). In this thesis, we were able to show significant speed enhancements for architectures as diverse …

    odu Repository record for Enhancing Portability in High Performance Computing: Designing Fast Scientific Code with Longevity (opens in a new tab)

  7. GPU-based acceleration of radio interferometry point source visibility simulations in the MeqTrees framework

    … radiation signals in deep space. While single dish radio telescopes convert the electromagnetic radiation directly into an image of the sky (or sky intensity map), interferometers convert the interference patterns between dishes in the array into samples of the Fourier plane (UV-data or …

    cape-town Repository record for GPU-based acceleration of radio interferometry point source visibility simulations in the MeqTrees framework (opens in a new tab)

  8. Applying Source Level Auto-Vectorization to Aparapi Java

    … This parallelism comes in the form of both data parallel single instruction multiple data (SIMD) instructions, as well as parallel compute cores in both central processing units (CPUs) and graphics processing units (GPUs). While these hardware enhancements offer potential performance …

    vt Repository record for Applying Source Level Auto-Vectorization to Aparapi Java (opens in a new tab)

  9. Speculative Vectorization with Selective Replay

    … again after the introduction of short vector instruction sets into general-purpose processors in the 1990s, and their successive improvement in subsequent architecture revisions. Single Instruction Multiple Data (SIMD) execution, where a single instruction operates on multiple data items, …

    cambridge Repository record for Speculative Vectorization with Selective Replay (opens in a new tab)

  10. Analytical Query Processing Based on Continuous Compression of Intermediates

    Nowadays, increasingly large amounts of data are being collected in numerous areas ranging from science to industry. To gain valueable insights from these data, the importance of Online Analytical Processing (OLAP) workloads is constantly growing. At the same time, the hardware landscape is …

    qucosa-diss

  11. Techniques to maximize memory bandwidth on the Rigel compute accelerator

    … processor chips. Currently GPUs that use wide SIMD are the primary implementations in this space. Many applications targeted to this space are performance limited by the memory all, so comparing the memory system performance of Rigel and GPUs is desirable. Memory controllers in GPUs attempt to …

    uiuc Repository record for Techniques to maximize memory bandwidth on the Rigel compute accelerator (opens in a new tab)

  12. A comparative study of the effects of parallelization on ARM and Intel based platforms

    … a processor level and involved making use of the multiple cores on a chip with OpenMP and Thread Building Blocks. We based the performance of the platforms on three metrics: throughput, energy per frame and throughput per energy, a metric similar to that of the energy-delay product. After …

    uiuc Repository record for A comparative study of the effects of parallelization on ARM and Intel based platforms (opens in a new tab)

  13. Effiziente SPH-basierte Flüssigkeitssimulation mit Visualisierung auf einem GPU-Cluster

    … welche die Instruktionen datenparallel per Single-Instruction-Multiple-Data (SIMD) abarbeiten. Deshalb sind sie für SPH-Simulationen gut geeignet. Auch sind die Speicherzugriffe einer SPH-Simulation extrem lokal. Deshalb eignen SPH-Simulationen sich auch sehr gut für einen GPU-Cluster. Es …

    bayreuth Repository record for Effiziente SPH-basierte Flüssigkeitssimulation mit Visualisierung auf einem GPU-Cluster (opens in a new tab)