Learn more about our state-of-the-art computing facility.
Why Use Eddie?
Eddie can cut the time taken to compute problems by running the software in parallel, or by breaking the problem into many pieces, each of which can be run on a separate cpu in parallel. Examples of the speed improvements that researchers have realised already are in Psychiatry, where processing of brain scans from a Schizophrenia study took 28 hours instead of 469 days, and a protein structure prediction study which involved 810,000 simulations and used 1.5 CPU years of computation in less than 2 days.
Users who wish to discuss their use of Eddie with the ECDF team should submit a query through the IS Helpline.
Eddie Linux Compute Cluster
Eddie Mark 3 is the third iteration of the University's compute cluster and is available to all University of Edinburgh researchers. It consists of some 4000 Intel® Xeon® cores with up to 2 TB of memory available per compute node.
GPGPU stands for General-Purpose computation on Graphics Processing Units. CUDA is a toolkit for GPGPU written by NVIDIA. OpenCL is a new industry standard programming system for developing parallel programs that typically execute on heterogeneous computing systems. Currently we have two compute nodes, each equipped with 2 x NVIDIA Tesla K80.
Symmetric Multiprocessing (SMP) and Large Memory Systems
Large memory jobs and shared memory programs using methods such as OpenMP (Open Multi-Processing) can make use of a range of memory offerings per node. We currently have compute nodes with 64GB, 128GB, 192GB, 256GB, 512GB, 768GB, and 2TB RAM