The School of Computer Science opened its newly renovated Teaching Assistant (TA) laboratory during their Open House on Tuesday September 19, 2023.
The university has invested in upgrading the undergraduate Computer Science labs and resources. The changes include a renovated TA center and BCS laboratories as well as further investment in the SCS Openstack cloud.
TA Center renovated
The TA Center has received a major upgrade. After a consultation process with students, lab coordinators and SCS staff the space was re-designed tailor fit for Teaching Assistant sessions. The new TA Center took inspiration from the popular Learning Lab at the Sauder School of Business at UBC (Image 2).
There was also a philosophical move away from providing lab machines to using laptops and cloud services. The renovated labs do not have computers, instead they have group stations designed for TA hours or group work using laptops.
The challenge was to offer hundreds of teaching assistants and a large number of students a space to efficiently run their TA hours. The teaching stations have been moved to the walls allowing easier flow of traffic in the center of the space (Image 1). The circular benching allows students to temporarily wait for their TA consultations. This will allow the space to accommodate many students and run TA hours efficiently.
The TA stations are equipped with USB and laptop power, back-lit lightboards, monitors and meeting cameras (Image 3). The lab has large south facing windows overlooking the scenic Rideau River.
The Openstack cloud resources service many of the SCS courses with their computing needs. Physical computers in labs have been replaced by laptops and virtual machines (VM’s). Some of the VM’s can be run directly on the student’s laptop and some are offered by connecting remotely to the SCS Openstack cloud.
The SCS Openstack cloud now runs 1,500 virtual CPU’s that are used by undergraduate courses at the school. In addition, the school has 60 GPU’s available for teaching Data Science, AI and gaming courses (Image 4).
Each GPU (Graphical Processing Unit) is a video card capable of running NVIDIA’s CUDA platform and can be used in programming data science applications in areas such as computer and machine vision, speech recognition, natural language processing, audio recognition, social network filtering, bioinformatics, drug design, and medical image analysis. The video cards can also be used in online gaming and video game testing and design.
The school of Computer Science Openstack cloud can support large number of students with their computer programming needs, something that would not have been possible using lab computers.
The resources are flexible so you can spin-up 100’s of lightweight VM’s that have one core and four gigabytes (GB) of memory, or you can spin up a single VM on our most powerful server with 128 vCPU’s, one terabyte (TB) of memory and can attach up to 100TB of storage space on a single VM. We offer leading edge resources to students that would normally not have at home or would be expensive on the Amazon cloud.
The School of Computer Science has invested in Data Science and AI and now runs the world’s fastest GPU: the NVIDIA RTX 4090 (Image 5). These resources are designed to be spun-up on demand for individual projects and/or class assignments. The most powerful GPU flavour can spin up four RTX4090 GPU’s, 256 GB of memory and 1 TB of local disk space. This VM has comparable processing power (teraflops – Tflops) as IBM Roadrunner, the 2008 Supercomputing champ: a whopping 764 Tflops of computing power.