The use of graphics processing units (GPUs) in high-performance parallel computing continues to steadily become more prevalent, often as part of a heterogeneous system. For years, CUDA has been the de facto programming environment for nearly all general-purpose GPU (GPGPU) applications. In spite of this, the framework is available only on NVIDIA GPUs, traditionally requiring reimplementation in other frameworks in order to utilize additional multi-or many-core devices. On the other hand, OpenCL provides an open and vendorneutral programming environment and run-time system. With implementations available for CPUs, GPUs, and other types of accelerators, OpenCL therefore holds the promise of a "write once, run anywhere" ecosystem for heterogeneous computing.Given the many similarities between CUDA and OpenCL, manually porting a CUDA application to OpenCL is almost straightforward, albeit tedious and error-prone. In response to this issue, we created CU2CL, an automated CUDA-to-OpenCL source-to-source translator that possesses a novel design and clever reuse of the Clang compiler framework. Currently, the CU2CL translator covers the primary constructs found in the CUDA Runtime API, and we have successfully translated several applications from the CUDA SDK and Rodinia benchmark suite. CU2CL's translation times are reasonable, allowing for many applications to be translated at once. The number of manual changes required after executing our translator on CUDA source is minimal, with some compiling and working with no changes at all. The performance of our automatically translated applications via CU2CL is on par with their manually ported counterparts.
Among many of the designs used in the detection of 2D gestures for portable technology, the touchpad is one of the most complex and with more functions to implement. Its development has undergone a great push due to its use in displays, but it is not widely used with other technologies. Its application on textiles could allow a wide range of applications in the field of medicine, sports, etc. Obtaining a flexible, robust touchpad with good response and low cost is one of the objectives of this work. A textile touchpad based on a diamond pattern design using screen printing technology has been developed. This technology is widely used in the textile industry and therefore does not require heavy investments. The developed prototypes were analyzed using a particular controller for projected capacitive technologies (pro-cap), which is the most used in gesture detection. Two different designs were used to obtain the best configuration, obtaining a good result in both cases.
There is an interest in new wearable solutions that can be directly worn on the curved human body or integrated into daily objects. Textiles offer properties that are suitable to be used as holders for electronics or sensors components. Many sensing technologies have been explored considering textiles substrates in combination with conductive materials in the last years. In this work, a novel solution of a gesture recognition touchless sensor is implemented with satisfactory results. Moreover, three manufacturing techniques have been considered as alternatives: screen-printing with conductive ink, embroidery with conductive thread and thermosealing with conductive fabric. The main critical parameters have been analyzed for each prototype including the sensitivity of the sensor, which is an important and specific parameter of this type of sensor. In addition, user validation has been performed, testing several gestures with different subjects. During the tests carried out, flick gestures obtained detection rates from 79% to 89% on average. Finally, in order to evaluate the stability and strength of the solutions, some tests have been performed to assess environmental variations and washability deteriorations. The obtained results are satisfactory regarding temperature and humidity variations. The washability tests revealed that, except for the screen-printing prototype, the sensors can be washed with minimum degradation.
RESUMENSobre el procesamiento digital de señales con sistemas de computadoras con capacidades genéricas, en su mayoría de un solo procesador multinúcleo Palabras clave: Procesamiento digital de señales, Algoritmos, Hardware paralelo Procesamiento Digital http://dx.
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