About Tariq Alturkestani Tariq Alturkestani Ph.D. Student, Computer Science High Performance Computing burst buffer optimization IO Tariq is a PhD student in Computer Science working under the supervision of Professor David E. Keyes. He is working on developing a library that enables users to overlap I/O and compute. Tariq holds a Bachelors degree from Penn State University and a Master from KAUST. Education Profile MS, Computer Science, King Abdullah University of Science and Technology (KAUST), 2014. BS, Computer Science, Penn State University, USA, 2013. Articles Related News July 2025 KAUST startup Saee delivers logistics innovation, reflecting University’s entrepreneurial impact 1 min read · Thu, Jul 24 2025 News Clip News From KAUST to acquisition by Estimkan, Saee’s journey underscores research-based entrepreneurship advancing national innovation. November 2020 KAUST startup aims to disrupt last-mile delivery 1 min read · Mon, Nov 30 2020 News As e-commerce continues to spike worldwide, especially with the pandemic, the number of parcels delivered each day has dramatically increased. Customer expectations for speedy fulfillment have also been rising, however, leaving companies to grapple with multiple, last-mile delivery challenges. Keep the data coming 1 min read · Mon, Nov 9 2020 News big data extreme computing applied mathematics computational science A continuous data supply ensures data-intensive simulations can run at maximum speed. September 2020 KAUST Ph.D. graduate wins best paper award at prestigious Euro-Par 2020 1 min read · Sun, Sep 20 2020 News Spotlight euro-par conference KAUST Ph.D. graduate, Dr Tariq Alturkestani, won the best paper award at the prestigious annual international conference Euro-Par 2020. The paper was selected out of 158 papers that were submitted by candidates from all over the world. August 2020 Tariq receives his best paper award at EuroPar'2020 1 min read · Thu, Aug 27 2020 News High Performance Computing GPU Computing burst buffer scientific computing Parallel and Distributed Computing Maximizing I/O Bandwidth for Out-of-Core HPC Applications on Heterogeneous Large-Scale Systems Best Paper Presentation by Tariq Alturkestani PhD Student, Computer Science, KAUST Thursday, Aug 27, 3:30pm - 4:00pm (AST) https://zoom.us/j/99947879910 Tariq will present his best paper at EuroPar'2020 at the virtual EuroPar'2020 conference in Warsaw, Poland. The reverse time migration (RTM) method is critical in seismic imaging for oil and gas industries. He demonstrates the effectiveness of his Multilayer Buffer System (MLBS) framework on Shaheen-2 (using 2048 compute nodes) and Summit
KAUST startup Saee delivers logistics innovation, reflecting University’s entrepreneurial impact 1 min read · Thu, Jul 24 2025 News Clip News From KAUST to acquisition by Estimkan, Saee’s journey underscores research-based entrepreneurship advancing national innovation.
KAUST startup aims to disrupt last-mile delivery 1 min read · Mon, Nov 30 2020 News As e-commerce continues to spike worldwide, especially with the pandemic, the number of parcels delivered each day has dramatically increased. Customer expectations for speedy fulfillment have also been rising, however, leaving companies to grapple with multiple, last-mile delivery challenges.
Keep the data coming 1 min read · Mon, Nov 9 2020 News big data extreme computing applied mathematics computational science A continuous data supply ensures data-intensive simulations can run at maximum speed.
KAUST Ph.D. graduate wins best paper award at prestigious Euro-Par 2020 1 min read · Sun, Sep 20 2020 News Spotlight euro-par conference KAUST Ph.D. graduate, Dr Tariq Alturkestani, won the best paper award at the prestigious annual international conference Euro-Par 2020. The paper was selected out of 158 papers that were submitted by candidates from all over the world.
Tariq receives his best paper award at EuroPar'2020 1 min read · Thu, Aug 27 2020 News High Performance Computing GPU Computing burst buffer scientific computing Parallel and Distributed Computing Maximizing I/O Bandwidth for Out-of-Core HPC Applications on Heterogeneous Large-Scale Systems Best Paper Presentation by Tariq Alturkestani PhD Student, Computer Science, KAUST Thursday, Aug 27, 3:30pm - 4:00pm (AST) https://zoom.us/j/99947879910 Tariq will present his best paper at EuroPar'2020 at the virtual EuroPar'2020 conference in Warsaw, Poland. The reverse time migration (RTM) method is critical in seismic imaging for oil and gas industries. He demonstrates the effectiveness of his Multilayer Buffer System (MLBS) framework on Shaheen-2 (using 2048 compute nodes) and Summit
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