8,691 research outputs found
FPGA-Based CNN Inference Accelerator Synthesized from Multi-Threaded C Software
A deep-learning inference accelerator is synthesized from a C-language
software program parallelized with Pthreads. The software implementation uses
the well-known producer/consumer model with parallel threads interconnected by
FIFO queues. The LegUp high-level synthesis (HLS) tool synthesizes threads into
parallel FPGA hardware, translating software parallelism into spatial
parallelism. A complete system is generated where convolution, pooling and
padding are realized in the synthesized accelerator, with remaining tasks
executing on an embedded ARM processor. The accelerator incorporates reduced
precision, and a novel approach for zero-weight-skipping in convolution. On a
mid-sized Intel Arria 10 SoC FPGA, peak performance on VGG-16 is 138 effective
GOPS
Generating optimized Fourier interpolation routines for density function theory using SPIRAL
© 2015 IEEE.Upsampling of a multi-dimensional data-set is an operation with wide application in image processing and quantum mechanical calculations using density functional theory. For small up sampling factors as seen in the quantum chemistry code ONETEP, a time-shift based implementation that shifts samples by a fraction of the original grid spacing to fill in the intermediate values using a frequency domain Fourier property can be a good choice. Readily available highly optimized multidimensional FFT implementations are leveraged at the expense of extra passes through the entire working set. In this paper we present an optimized variant of the time-shift based up sampling. Since ONETEP handles threading, we address the memory hierarchy and SIMD vectorization, and focus on problem dimensions relevant for ONETEP. We present a formalization of this operation within the SPIRAL framework and demonstrate auto-generated and auto-tuned interpolation libraries. We compare the performance of our generated code against the previous best implementations using highly optimized FFT libraries (FFTW and MKL). We demonstrate speed-ups in isolation averaging 3x and within ONETEP of up to 15%
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