Energy-Efficient Collective Reduce and Allreduce Operations on Distributed GPUs. - Lena Oden; Benjamin Klenk; Holger Fröning (CCGRID, 2014)

Analyzing Put/Get APIs for Thread-Collaborative Processors. - Benjamin Klenk; Lena Oden; Holger Fröning (ICPP Workshops, 2014)

Energy-efficient stencil computations on distributed GPUs using dynamic parallelism and GPU-controlled communication. - Lena Oden; Benjamin Klenk; Holger Fröning (E2SC@SC, 2014)

Analyzing communication models for distributed thread-collaborative processors in terms of energy and time. - Benjamin Klenk; Lena Oden; Holger Fröning (ISPASS, 2015)

Analyzing GPU-controlled communication with dynamic parallelism in terms of performance and energy. - Lena Oden; Benjamin Klenk; Holger Fröning (Parallel Comput., 2016)

Relaxations for High-Performance Message Passing on Massively Parallel SIMT Processors. - Benjamin Klenk; Holger Fröning; Hans Eberle; Larry Dennison (IPDPS, 2017)

An Overview of MPI Characteristics of Exascale Proxy Applications. - Benjamin Klenk; Holger Fröning (ISC, 2017)

Communication architectures for scalable GPU-centric computing systems. - Benjamin Klenk (2018)

An In-Network Architecture for Accelerating Shared-Memory Multiprocessor Collectives. - Benjamin Klenk; Nan Jiang 009; Greg Thorson; Larry Dennison (ISCA, 2020)

Why Data Science and Machine Learning Need Silicon Photonics. - Benjamin Klenk; Larry Dennison (OFC, 2020)

SiP-ML: high-bandwidth optical network interconnects for machine learning training. - Mehrdad Khani Shirkoohi; Manya Ghobadi; Mohammad Alizadeh; Ziyi Zhu; Madeleine Glick; Keren Bergman; Amin Vahdat; Benjamin Klenk; Eiman Ebrahimi (SIGCOMM, 2021)

A Case For Intra-rack Resource Disaggregation in HPC. - George Michelogiannakis; Benjamin Klenk; Brandon Cook 001; Min Yee Teh; Madeleine Glick; Larry Dennison; Keren Bergman; John Shalf (ACM Trans. Archit. Code Optim., 2022)

Towards a Standardized Representation for Deep Learning Collective Algorithms. - Jinsun Yoo; William Won; Meghan Cowan; Nan Jiang; Benjamin Klenk; Srinivas Sridharan 002; Tushar Krishna (HOTI, 2024)

Toward a Standardized Representation for Deep Learning Collective Algorithms. - Jinsun Yoo; William Won; Meghan Cowan; Nan Jiang; Benjamin Klenk; Srinivas Sridharan 002; Tushar Krishna (IEEE Micro, 2025)