Doctorate in Computational Sciences Tools and Software
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Modified on: Fri, 9 Jan, 2026 at 11:17 AM

The following tools and software are used specifically by Doctorate in Computational Sciences (CSDR) students at Harrisburg University. At any point you can return to the Overview - Supported Software and Tools page.
Tool
| Description
| Support
|
|---|
| Parallel Computing and Hardware-Optimized AI |
|
|
| CUDA (Compute Unified Device Architecture) | CUDA provides parallel computing capabilities for AI/ML training and inference. It is used for neurocomputing acceleration, HPC, and AI inference.
| Internal: Your class Faculty
Other: NVIDIA developer forums, internal DevOps |
OpenCL (Open Computing Language)
| OpenCL is an open-source framework enabling parallel programming across heterogeneous hardware. It is used for AI acceleration on non-NVIDIA hardware.
| Internal: Your class Faculty
Other: Khronos Group, vendor documentation |
MPI (Message Passing Interface)
| MPI is used for deep learning models and enables multi-node parallelism for AI training on HPC clusters
| Internal: Your class Faculty
Other: MPI open-source community, internal cluster team |
Eigen (C++ Linear Algebra Library)
| Integrated into TensorFlow C++ for fast inference and optimized for matrix operations. | Internal: Your class Faculty
Other: Eigen GitHub, TensorFlow docs
|
| AI Model Parallelization |
|
|
Horovod (Uber's Distributed Training Framework)
| Horovod Framework for distributed deep learning training is used for training LLMs on multiple GPUs. | Internal: Your class Faculty
Other: Uber Horovod GitHub, OpenAI docs
|
NCCL (NVIDIA Collective Communications Library)
| NCCL accelerates multi-GPU training using optimized interconnects for deep learning. | Internal: Your class Faculty
Other: NVIDIA dev forums, internal DevOps. |
Ray Train (Ray.io for Distributed Training)
| Distributed training library supporting scalable deep learning and large-scale models.
| Internal: Your class Faculty
Other: Eigen GitHub, TensorFlow docs |
| FPGA-Based AI |
|
|
Intel OpenVINO
| Intel OpenVINO is an AI optimization toolkit for real-time inference that accelerates AI inference workloads on edge devices.
| Internal: Your class Faculty
Other: Intel DevCloud, OpenVINO community
|
Xilinx Vitis AI
| Xilinx Vitis AI is a hardware acceleration platform for AI inference on Xilinx FPGAs. It is used in low-power edge AI applications.
| Internal: Your class Faculty
Other: Xilinx forums, FPGA optimization guides
|
Ray Train (Ray.io for Distributed Training)
| Distributed training library supporting scalable deep learning. Used in large-scale model and reinforcement training.
| Internal: Your class Faculty
Other: Ray community forums, open-source contributors
|
| Edge AI & AI Inference |
|
|
TensorRT (NVIDIA)
| TensorRT optimizes AI inference performance for low-latency, real-time applications.
| Internal: Your class Faculty
Other: NVIDIA Dev Forums |
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