Algorithmic Techniques for Scalable Many Core Computing

Wen-Mei Hwu, University of Illinois at Urbana-Champaign

Usage Details

Wen-Mei Hwu, Blue Waters Trainee 325, Blue Waters Trainee 326, Blue Waters Trainee 327, Blue Waters Trainee 328, Blue Waters Trainee 329, Blue Waters Trainee 330, Blue Waters Trainee 331, Blue Waters Trainee 332, Blue Waters Trainee 333, Blue Waters Trainee 334, Blue Waters Trainee 335, Blue Waters Trainee 336, Blue Waters Trainee 337, Blue Waters Trainee 338, Blue Waters Trainee 339, Blue Waters Trainee 340, Blue Waters Trainee 341, Blue Waters Trainee 342, Blue Waters Trainee 343, Blue Waters Trainee 344, Blue Waters Trainee 345, Blue Waters Trainee 346, Blue Waters Trainee 347, Blue Waters Trainee 348, Blue Waters Trainee 349, Blue Waters Trainee 350, Blue Waters Trainee 351, Blue Waters Trainee 352, Blue Waters Trainee 353, Blue Waters Trainee 354, Blue Waters Trainee 355, Blue Waters Trainee 356, Blue Waters Trainee 357, Blue Waters Trainee 358, Blue Waters Trainee 359, Blue Waters Trainee 360, Blue Waters Trainee 361, Blue Waters Trainee 362, Blue Waters Trainee 363, Blue Waters Trainee 364, Blue Waters Trainee 365, Blue Waters Trainee 366, Blue Waters Trainee 367, Blue Waters Trainee 368, Blue Waters Trainee 369, Blue Waters Trainee 370, Blue Waters Trainee 371, Blue Waters Trainee 372, Blue Waters Trainee 373, Blue Waters Trainee 374, Blue Waters Trainee 375, Blue Waters Trainee 376, Blue Waters Trainee 377, Blue Waters Trainee 378, Blue Waters Trainee 379, Blue Waters Trainee 380, Blue Waters Trainee 381, Blue Waters Trainee 382, Blue Waters Trainee 383, Blue Waters Trainee 384, Blue Waters Trainee 385, Blue Waters Trainee 386, Blue Waters Trainee 387, Blue Waters Trainee 388, Blue Waters Trainee 389, Blue Waters Trainee 390, Blue Waters Trainee 391, Blue Waters Trainee 392, Blue Waters Trainee 393, Blue Waters Trainee 394, Blue Waters Trainee 395, Blue Waters Trainee 396, Blue Waters Trainee 397, Blue Waters Trainee 398, Blue Waters Trainee 399, Blue Waters Instructor 001, Blue Waters Instructor 002

The course is designed to teach graduate students in science and engineering disciplines with computational thinking and algorithm design skills needed to use computing clusters with many-core GPUs to solve their domain problems. The lectures and lab assignments will also cover joint MPI-CUDA programming needed for using such as a cluster. It is also designed to teach graduate students in computer engineering and computer science common domain models and algorithms used in science and engineering applications. This can be especially beneficial for students whose research is in parallel programming tools and libraries.