To promote awareness of its researchers and their work at next week’s International Conference for High Performance Computing, Networking, Storage, and Analysis – widely known as Supercomputing (SC) – Georgia Tech has created Superheroes of Supercomputing trading cards.

“Georgia Tech is using high-performance computing (HPC) to help solve some of the world’s toughest technical challenges in energy, sustainability, human health, materials science, and national security,” said Center for High Performance Computing Director and School Computational Science and Engineering (CSE) Professor Rich Vuduc.

“We believe research this powerful deserves the superhero treatment. So, we have created the first-ever Superheroes of Supercomputing card deck to showcase Georgia Tech's HPC findings.”

Each card represents one of four technical papers being presented at SC’18, which is being held in Dallas, Texas, Nov. 11 to 16. A card touting the Rogue’s Gallery, Georgia Tech’s growing collection of next generation computing hardware – has also been created.

Along with a unique superhero for each subject, the two-sided cards include details about the project and list the primary researchers along with their Georgia Tech affiliations. All artwork and design work was done by Georgia Tech communications officer Kristen Perez.

Also included on each card are details about how SC’18 conference attendees can enter a contest for the chance to win an Amazon Echo Show courtesy of Amazon through the cards. To enter, attendees can take a photo of any character from the deck out in the world, at home, or at the conference itself and post to Twitter or Instagram with the hashtag: #gtsuperherosc18. Downloadable PDF versions are available online for printing purposes. Winners will be announced Nov. 28. 

The paper and center contributions, each with a representative superhero card, are below. A complete list of Georgia Tech activities at SC’18 can be viewed here.

• Rogues Gallery
• HiCOO: Hierarchical Storage of Sparse Tensors
• Accelerating Quantum Chemistry with Vectorized and Batched Integrals
• Detecting MPI Usage Anomalies via Partial Program Symbolic Execution
• Optimizing High Performance Distributed Memory Parallel Hash Tables for DNA k-mer Counting