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Floating Point Arithmetic is Not Real
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Details
Learning objectives: Attendees will leave with a basic understanding of computer representation of numbers, a basic understanding of floating point arithmetic, the consequences of floating point arithmetic for scientific computing and a basic understanding about fast math.
Knowledge prerequisites:Basic C/C++ knowledge.
Hardware/software prerequisites: (1) Bring a laptop which can connect to the eduroam wireless network. You will also need to be able to Duo authenticate to use campus resources. (2) Have an SSH client (https://researchcomputing.princeton.edu/learn/workshops-live-training/hardware-and-software-requirements-picscie-workshops) installed on your laptop. (3) Register for an account on Adroit (https://forms.rc.princeton.edu/registration/). This is the cluster we will use for demonstration purposes. Make sure you can SSH to Adroit before the workshop by following this guide. (https://researchcomputing.princeton.edu/learn/workshops-live-training/hardware-and-software-requirements-picscie-workshops)
Workshop format: Lecture and hands-on
Speakers
Bei Wang
Princeton University
Bei Wang is a Senior Research Software Engineer in the Research Computing Department at Princeton University. She is currently working on projects to speed up the process of particle tracking on modern CPUs, GPUs and FPGAs in the IRIS-HEP program. She is also a co-PI of the Intel Parallel Computing Center (IPCC) of Princeton University. She received a Ph.D. in applied science with designed emphasis on computational science and engineering from the University of California at Davis.
Hosted By
Co-hosted with: GradFUTURES
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