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OpenCL has become the favored framework for emerging heterogeneous devices and FPGAs, owing to its versatility and portability.
However, OpenCL-based math libraries still face challenges in fully leveraging device performance.
When deploying high-performance arithmetic applications on these devices, the most important hot function is General Matrix-matrix Multiplication (GEMM).
This study presents a meticulously optimized OpenCL GEMM kernel.
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This dataset has been taken using the Photonic Mixer Device (PMD) Selene Module. To capture the image, we have constructed a demonstrator setup consisting of five materials (i.e., foam board (location: center), crepe paper (location: top), polystyrene (location: right), bubble wrap (location: left), wax (location: bottom)). Each image has been taken at 5 different distances (uniformly distributed between 82 cm to 47 cm) and at 3 different orientations (uniformly distributed between -10 degree to 10 degree) for each material. To avoid noise, each image has been taken in dark environment.
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The measurement dataset consists of reflected received power from different shaped and sized metallic reflectors at 28 GHz in the indoor corridor and outdoor open area. PXI channel sounder from National Instruments was used for measurements. Horn antennas of gain 17 dBi were used at the transmitter and receiver. The measurements consisted of three flat square metallic reflectors of sizes 0.84 × 0.84 m^2 , 0.61 × 0.61 m^2 , and 0.3 × 0.3 m^2 , a sphere, and a cylinder. The effect of size and shape of the reflectors on the coverage was analyzed in the indoor corridor and outdoor open area.
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