This project explores the possibilities of using attention-based transformer models to aid in tasks related to data visualization and interpretation, through the use of various Intel oneAPI toolkits such as the DNN library, oneAPI AI Kit, as well as oneAPI Render Kit.
Current HLS tools fail to synthesise efficient architectures for irregular codes because they rely on
static scheduling. Elastic dataflow techniques enable circuits to be scheduled dynamically and achieve
a higher performance in accelerating irregular codes.
Significant business decisions is taken based on the outcome predicted by the ML model. Users get benefit from an unbiased, statistically sound and rigorous re-validation of the prediction’s accuracy from an independent source. That is what the Predictive Risk Analyzer tool from Quantic aims to go.
This concept drift project is run on video and image datasets such that we can calculate an overall precision and standard error.
The concept drift detection technique finds True positives and False negatives using real and virtual drift detection.
This project targets specifically the acceleration of the pairwise alignment algorithms and pattern matching algorithms contained in the SeqAn library.
Dpctl provides Python SYCL bindings and SYCL-based Python Array API library. The dpctl simplifies building Python native extensions that use oneAPI DPC++ to implement portable data-parallel functions, as well as implements such extensions for its array library.
toyBrot is a raymarching fractal generator that is used both as a simple benchmarking tool and a study tool for parallelisation. The code is is implemented with over 10 different technologies, including Intel TBB, ISPC and SYCL (with support for oneAPI)
Phase field technique is used to simulate microstructure evolution during materials processing such as 3D printing and additive manufacturing apart from traditional manufacturing techniques like welding, casting etc. These non-linear PDE solvers are compute intensive and also memory intensive.
This work aims to accelerate the different stages involved in FPGA placement - global placement, legalization and detailed placement, using the Pytorch deep-learning toolkit. Placement in the FPGA design flow determines the physical locations of all the heterogeneous instances in the design.
Neural style transfer is an optimization technique used to take two images—a content image and a style reference image (such as an artwork by a famous painter)—and blend them together so the output image looks like the content image, but “painted” in the style of the style reference image.
Accelerate data mining and deep learning applications via Intel onapi. Provide sample code and examples in SJSU CMPE255 Data Mining class (https://catalog.sjsu.edu/preview_course_nopop.php?catoid=12&coid=58423) to demonstrate the importance of acceleration and use Intel OneAPI as one technological e
This is a program i designed to plot the Mandelbrot set, it can do this either with 1 thread, all threads or utilising SYCL via intels DPC++ compiler included in OneAPI toolkit to use GPU acceleration.