Marcus Rogers
Vice President at Purdue University
West Lafayette, Indiana, United States
Summary
🤩
Rockstar🎓
Top SchoolMarcus Rogers is a vice president and seasoned academic leader with 14 years of experience at the intersection of forensic psychology, digital forensics, and computer engineering. Based at Purdue and now serving as Vice President of the American Academy of Forensic Sciences, he directs cyberforensics programs, leads faculty initiatives, and has held multiple interim and departmental leadership roles across Purdue Polytechnic. His rare blend of PhD-level forensic psychology and hands-on systems work is reflected in low-level contributions to prominent GPU simulation projects (GPGPU-Sim and Accel-Sim), where he optimized CUDA/OpenCL performance and strengthened simulation telemetry. Marcus combines scholarly rigor—University of Manitoba PhD—with practical lab leadership, mentoring students and shaping cybersecurity apprenticeship programs. Colleagues know him for translating complex hardware-software behaviors into actionable forensic analysis and for expanding measurable statistics in research-grade simulators.
14 years of coding experience
6 years of employment as a software developer
PhD Psychology - Forensic, PhD Psychology - Forensic at University of Manitoba
English
Github Skills (9)
cuda10
c-language10
cprogramming-language10
gpu10
performance-optimization10
python9
opencl9
memory-management9
web-framework9
Programming languages (7)
Github contributions (5)
accel-sim/accel-sim-framework
Jun 2017 - Jun 2022
This is the top-level repository for the Accel-Sim framework.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5 releases, 48 reviews, 962 commits in 5 years 1 month
Contributions summary:Marcus primarily focused on improving the Accel-Sim framework, specifically by addressing bugs in job launching and status monitoring. Their contributions included bug fixes for argument handling, improvements to the display and logging of job statuses, and the implementation of a more versatile system for obtaining statistics. They also refactored the system to simplify the gathering of statistics and expanded the scope of tracked statistics.
pythongraphical-user-interfacehpc-applicationsaccelsim
gpgpu-sim/gpgpu-sim_distribution
Jun 2011 - May 2021
GPGPU-Sim provides a detailed simulation model of contemporary NVIDIA GPUs running CUDA and/or OpenCL workloads. It includes support for features such as TensorCores and CUDA Dynamic Parallelism as well as a performance visualization tool, AerialVisoin, and an integrated energy model, GPUWattch.
Role in this project:Back-end Developer
Back-end DeveloperContributions:2 releases, 526 commits, 51 PRs in 10 years
Contributions summary:Marcus's commits primarily involve modifications to the GPGPU-Sim simulator, focusing on improving the performance of CUDA kernels through optimizations to memory access patterns and instruction counting. Their work involved adding stats for memory divergence and addressing issues related to instruction counting when cache configurations changed. They also made significant changes to the OpenCL integration. The user’s changes extended to low-level hardware and architecture modeling.
simsimulationgpgpuopenclnvidia
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