Technology The Durham College GPU Accelerate AI Systems Lab Durham College is well-positioned to grow as a leader in helping companies to develop and adopt AI solutions. A GPU accelerated AI computing lab was established in 2017, including a large capacity GPU-based computer system, for teaching and research applications in machine and deep learning. Students trained in this lab will bring advanced practice to projects with local businesses. In addition to its on-campus resources, the AI Hub offers expertise and access to industry-leading, domain-specific AI platforms that address a variety of business use cases that are undertaken in industry projects. GPU Accelerated Platform The Durham College GPU Accelerated compute system is an IBM Power8 server with state-of-the-art NVIDIA Tesla GPUs. The IBM Power8 system uses the NVLINK technology to provide high-bandwidth connection between the core compute tasks in the CPU, system memory, and the GPU compute tasks. This system is used primarily for research, project work and teaching in the fields of machine learning and deep learning where the multiple-GPU cores can be used in parallel to achieve high throughput model development. Technical Specifications Model IBM Power System S822LC for HPC and AI Number of nodes 1 CPUs Dual POWER8 10Core Processor GPUs Two Nvidia Tesla P100 GPUs System Memory 512GB Storage Dual 480GB Read Intensive SATA 5xx SFF-4 SSD (mirror) Operating System Ubuntu (Linux) ML Software IBM Power AI (includes Caffe, TensorFlow, Theano, Torch, Chainer, DIGITS, OpenBLAS, Bazel, NCGL, NVIDIA CUDA) System Software Python, Jupyter Notebook, Keras ARC Compute Cluster (pay per use) High performance virtual machines. Capable of up to 16 vGPU’s per physical GPU, Latest AMD and NVIDIA hardware – developments for a wide variety of enterprise applications, production workloads, Connection speeds (over VNC client) of up to 1200 FPS. SHARCNET 41,548 cores and 520 GPU devices, 1,185 nodes of different configurations. GPU Clusters P100 Pascal GPUs V100 Volta GPUs (including 2 nodes with NVLINK interconnect) T4 Turing GPUs All computing clusters are strictly for development only. The AI Hub also maintains skillsets in deployments clusters across AWS, Azure and other private cloud ecosystems. Processor: Intel Core i7–9750h up to 4.5 GHz. Memory: 16 GB DDR4. Hard Drives: 256 GB NVMe SSD. GPU: NVIDIA GeForce RTX 2060 6 GB. Computing Power: 7.5 Ports: 1x HDMI 2.0, 1x USB 3.1 Type-C, 2x USB 3.1, 1x USB 2.0. OS: Windows 10. Weight: 4.85 lbs. Display: 15.6, 1920 x 1080. Connectivity: WiFi 802.11ax, Gigabit LAN (Ethernet), Bluetooth.