Ivy Peng, Ph.D
Associate Professor in Computer Science
Department of Computer Science
EECS, KTH
I lead the Scalable Computing Laboratory (ScaLab) at KTH, Sweden. My research interests revolve around the scalability and efficiency of future computing systems, including computer architecture, system software, and applications. Previously, I was a Computer Scientist at Parallel System Group at Lawrence Livermore National Laboratory, California, USA.
Current Research Topics:
- Heterogeneous computing (e.g., smartNIC, DPU, GPU, RISC-V accelerators).
- Memory-centric computing (e.g., disaggregated memory, CXL, NVM, heterogeneous memories).
- Converged HPC and cloud computing (e.g., elasticity, malleability, optimizations).
Recent Professional Services:
- IEEE Transactions on Parallel and Distributed Systems (TPDS). Editorial Review Board.
- The 53rd International Conference on Parallel Processing (ICPP’24). Technical Program co-Chair.
- International Conference for High Performance Computing, Networking, Storage, and Analysis (SC’23). Proceeding Chair.
- ACM Symposium on High-Performance Paralleland Distributed Computing (HPDC’21,HPDC’22). Workshop Chair.
- ACM International Conference on Supercomputing (ICS’24). Main PC.
- ACM Symposium on High-Performance Paralleland Distributed Computing (HPDC’24). Main PC.
- International Conference for High Performance Computing, Networking, Storage, and Analysis (SC’24). Main PC.
- ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP’23). Main PC.
Jacob Wahlgren
Doctoral Student
Department of Computer Science
EECS, KTH
Heterogeneous Computing, High-Performance Computing
About me:
My current research revolves around next-generation memory systems in high-performance computing. Disaggregated memory promises to increase the efficiency of cloud data centers by using rack-scale memory pools. We aim to answer questions such as: How can we utilize memory disaggregation in supercomputing enviroments? How will memory disaggregation impact the performance of scientific workloads such as computational physics? What new acceleration techniques are enabled by disaggregated systems?
My current research revolves around next-generation memory systems in high-performance computing. Disaggregated memory promises to increase the efficiency of cloud data centers by using rack-scale memory pools. We aim to answer questions such as: How can we utilize memory disaggregation in supercomputing enviroments? How will memory disaggregation impact the performance of scientific workloads such as computational physics? What new acceleration techniques are enabled by disaggregated systems?
Daniel Araújo de Medeiros
Doctoral Student
Department of Computer Science
EECS, KTH
Parallel I/O, Converged Cloud and HPC Computing
About me:
I'm Daniel, a doctoral student at KTH. My field of study is High Performance Computing and, as implied, I deal with a lot of problems in relation to parallel and distributed systems. I research on technologies that are used in warehouse-scale computers ("datacenters") and could be used in traditional supercomputers on academic settings. Such technologies ranges from the usage of kubernetes and containers to object storage systems. Furthemore, I have strong interests in non-traditional computer architectures and stuff like binary translation/emulation.
I'm Daniel, a doctoral student at KTH. My field of study is High Performance Computing and, as implied, I deal with a lot of problems in relation to parallel and distributed systems. I research on technologies that are used in warehouse-scale computers ("datacenters") and could be used in traditional supercomputers on academic settings. Such technologies ranges from the usage of kubernetes and containers to object storage systems. Furthemore, I have strong interests in non-traditional computer architectures and stuff like binary translation/emulation.
Gabin Schieffer
Doctoral Student
Department of Computer Science
EECS, KTH
Heterogeneous Computing, Parallel Algorithms, GPU
About me:
Bonjour! My research focus on GPU acceleration of scientific applications. I am also interested in distributed computing, in both HPC clusters and cloud computing environments. My current work aims at enabling the use of novel GPU features to accelerate typical high-performance computing workloads, such as molecular docking applications.
Bonjour! My research focus on GPU acceleration of scientific applications. I am also interested in distributed computing, in both HPC clusters and cloud computing environments. My current work aims at enabling the use of novel GPU features to accelerate typical high-performance computing workloads, such as molecular docking applications.
Jennifer Faj
Doctoral Student
Department of Computer Science
EECS, KTH
Heterogeneous Computing, Parallel Algorithms, FPGA
About me:
Louise Tidestav
MS Student
Department of Computer Science
EECS, KTH
A Domain Specific Language for Geospatial GPU Calculations
Philip Salqvist
MS Student
Department of Computer Science
EECS, KTH
A comparative study of the Data Warehouse and Data Lakehouse architecture
Federico Ruilova
MS Student
ICT Innovation – Cloud and Network Infrastructures
EECS, KTH
Carbon-aware technologies for high-performance computing in distributed environments
About me:
Jakob Arvidsson
MS Student
Department of Computer Science
EECS, KTH
Simulated Molecular Adder Circuits on a Surface of DNA -- Studying the scalability of surface chemical reaction network digital logic circuits