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ARM Cortex-A9 performance in HPC applications Kurt Keville, Clark Della Silva, Merritt Boyd

ARM Cortex-A9 performance in HPC applications Kurt Keville, Clark Della Silva, Merritt Boyd. ARM gaining market share in embedded systems and SoCs Current processors include the ARM9 series, the Cortex-A8, and the Cortex-A9 ~15 Billion ARM chips shipped to date Thumb / Thumb-2

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ARM Cortex-A9 performance in HPC applications Kurt Keville, Clark Della Silva, Merritt Boyd

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  1. ARM Cortex-A9 performance in HPC applicationsKurt Keville, Clark Della Silva, Merritt Boyd ARM gaining market share in embedded systems and SoCs Current processors include the ARM9 series, the Cortex-A8, and the Cortex-A9 ~15 Billion ARM chips shipped to date Thumb / Thumb-2 More efficient instruction encoding, better code density Higher performance for select applications VFPv3 Floating point co-processor NEON SIMD Extensions Up to 4x 32-bit floating point operations per instruction No double precision

  2. ARM Cortex-A8 and Cortex-A9 Uses the ARMv7-A architecture Thumb-2, NEON, VFPv3 Systems TI BeagleBoard (1GHz)‏ Genesi Efika-MX (800MHz)‏ Gumstix Overo Earth (600MHz)‏ • Uses ARMv7-A architecture • Thumb-2, NEON, VFPv3 • Available in single and dual core packages, quads upcoming (A6, Tegra 3)‏ • Systems • TI PandaBoard (dual 1GHz)‏ • NuFront NuSmart (dual 1.2GHz)‏

  3. TI PandaBoard Results 3.0 Gflop/s SP NEON, 1.2 Gflop/s DP (HPL)‏ Power consumption Idle: ~4 Watts / board, Full load: ~7.5 Watts / board Software & Hardware Challenges Most libraries assume x86 / x86-64, No precompiled binaries (unavailable or unoptimized), Compiler support immature (-mcpu=cortex-a9, -mhard-float)‏ Limited RAM on some systems, Low-quality networking hardware and software, Few possibilities for expansion, Reliability issues Energy Efficiency 2 Gflop/s / Watt gets you #1 on Green500 PandaBoard is $175, and 18 square inches .4 Gflop/s / Watt, 0.0074 Gflop/s / $, and 0.072 Gflop/s / square inch

  4. Looking Ahead : Embedded GPUs Most SoCs include a GPU, e.g. PVR SGX 540 (PandaBoard)‏ Potential for mixed CPU-GPU computation OpenCL support, pending release of drivers on TI SoCs, available for Apple Hardware ARM Cortex-A15 with PVR series 6 GPU Much more powerful and better suited for computation Tegra 3 & 4 Potential for Cuda Support

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