Some shapes will need to be held with string, rubber bands or hot-glue until dry. And only 1/32” sheets can be cut with scissors.įor faster drying use a hair dryer, or place in front of a room fan. Yet if you slightly spray both sides with water, you will be able to form and shape it into curvilinear 3D objects that will become rigid when dry.Īll sheets are formable except 1/8” thick sheets. Taskboard is stable, flat and will not warp. With scissors, craft-knife, or laser cutter - these low-density sheets are extremely easy to cut.įor those using a laser cutter, Taskboard® cuts much faster than all other materials and with minimal, light-colored scorch marks. Automatically exploiting short vector instructions sets (SSE, AVX, NEON) is a critically important task for optimizing compilers.Taskboard is a low-density sheet material made from sustainable forestry wood. Vector instructions typically work best on data that is contiguous in memory, and operating on non-contiguous data requires additional work to gather and scatter the data. There are several varieties of non-contiguous access, including interleaved data access. An existing approach used by GCC generates extremely efficient code for loops with power-of-2 interleaving factors (strides). In this paper we propose a generalization of this approach that produces similar code for any compile-time constant interleaving factor. In addition, we propose several novel program transformations, which were made possible by our generalized representation of the problem. Experiments show that our approach achieves significant speedups for both power-of-2 and non-power-of-2 interleaving factors. Our vectorization approach results in mean speedups over scalar code of 1.77x on Intel SSE and 2.53x on Intel AVX2 in real-world benchmarking on a selection of BLAS Level 1 routines. On the same benchmark programs, GCC 5.0 achieves mean improvements of 1.43x on Intel SSE and 1.30x on Intel AVX2. In synthetic benchmarking on Intel SSE, our maximum improvement on data movement is over 4x for gathering operations and over 6x for scattering operations versus scalar code. Code generation using tree matching and dynamic programming. ACM Transactions on Programming Languages and Systems (TOPLAS) 11, 4 (1989), 491-516. Efficient retargetable code generation using bottom-up tree pattern matching.Rajkishore Barik, Jisheng Zhao, and Vivek Sarkar.Efficient selection of vector instructions using dynamic programming.Albert Cohen, Sylvain Girbal, and Olivier Temam. A polyhedral approach to ease the composition of program transformations. Eichenberger, Peng Wu, and Kevin O’Brien. Vectorization for SIMD architectures with alignment constraints.Liza Fireman, Erez Petrank, and Ayal Zaks.A SIMD vectorizing compiler for digital signal processing algorithms. In Proceedings of the 1993 IEEE Vehicle Navigation and Information Systems Conference. BURG: Fast optimal instruction selection and tree parsing. Generation of permutations for SIMD processors. Exploiting superword level parallelism with multimedia instruction sets. Basic linear algebra subprograms for Fortran usage. #Taskboard architecture material used scholar software#ĪCM Transactions on Mathematical Software (TOMS) 5, 3 (1979), 308-323. Jun Liu, Yuanrui Zhang, Ohyoung Jang, Wei Ding, and Mahmut T.Accelerating multimedia with enhanced microprocessors. Saeed Maleki, Yaoqing Gao, María Jesús Garzarán, Tommy Wong, and David A.A compiler framework for extracting superword level parallelism. Auto-vectorization of interleaved data for SIMD. How to Benchmark Code Execution Times on Intel IA-32 and IA-64 Instruction Set Architectures. Yongjun Park, Sangwon Seo, Hyunchul Park, Hyoun Kyu Cho, and Scott Mahlke.SIMD defragmenter: Efficient ILP realization on data-parallel architectures. In ACM SIGARCH Computer Architecture News, Vol. Optimizing data permutations for SIMD devices. Discrete Mathematics and Its Applications (7th ed.).Thomas Schaub, Simon Moll, Ralf Karrenberg, and Sebastian Hack.The impact of the SIMD width on control-flow and memory divergence. #Taskboard architecture material used scholar code#ĪCM Transactions on Architecture and Code Optimization (TACO) 11, 4 (2015), 54.#Taskboard architecture material used scholar software#.#Taskboard architecture material used scholar how to#.
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