The platform is a network of General Purpose Compute Nodes designed by the Distributed Computing Research Group at Balanced City. ¹ Compute Node Architecture · Overview A Compute Node is a group of computers that works together on large projects. Distributed computing research and experience in performance engineering guided the design of the General Purpose Compute Node GPCN2021. General Purpose Compute Node GPCN2021 A General Purpose Compute Node has 15 computers, pictured above. · 12 x RPi A+ Primary Computers perform the scientific work that the system is designed to accomplish. · 3 x RPi B Managers orchestrate workflow, data and communication. 12 x Raspberry Pi Model A+
64bit ARM Cortex-53
Quad-Core 1.4GHz
3 x Raspberry Pi Model B
64bit ARM Cortex-A72
Quad-Core 1.5 GHz
Each individual RPi has a Quad-Core Processor with 4 Central Processing Unit (CPU) Cores. Each CPU Core can perform an independent computational task. A General Purpose Compute Node has a total of 60 CPU Cores. Compute Node Workflow · Primary Computation RPi B Managers divide the workload into partitions, preparing data and computational tasks for up to 48 CPU Cores on 12 RPi A+ Primary Computers. Primary Computers deliver processed data back to Managers upon completion. Managers consolidate processed data, checking for accuracy and consistency. Lastly, managers send processed data from the Compute Node to the project's final inventory. Compute Node Software · Scientific Libraries, Methods and Tools Scientific libraries, methods and tools used on this architecture are created de novo and inspired by leadership initiatives of the NIH Biowulf Cluster ² and Department of Energy National Laboratories ³. · Applications applications support scientific research and are developed with databases from the National Center for Biotechnology Information, a division of the National Library of Medicine at the National Institutes of Health in the United States. These applications are collectively referred to as the Learning Health Systems and are accessible by client applications such as This machine teaching platform benefits from natural intelligence of users around the world. Operational Performance · Initial Deployment Compute Nodes began operation in Q2 2019 performing CPU intensive language processing for the Learning Health Systems. · Utilitization The utilization profile of a Compute Node typically has 20 to 35 CPU Cores in continuous parallel operation for several hours up to several days. Technical measures of processor speed are less relevant than the number of independent tasks performed simultaneously. · Developer Productivity Engineered to maximize performance of developers through automation and ease of use, Compute Node Architecture eliminates productivity barriers for rapid prototyping, programming, optimizing and deploying supercomputing systems. Easily deploying 1,000 computational tasks with no complexity burden is a practical measure of system success from the perspective of a developer. · Operations per second Computing benchmarks measure floating-point operations per second (FLOPS). The Compute Nodes described here are capable of... · 64 GigaFLOPS peak CPU primary computation · 85 GigaFLOPS peak CPU total computation Sustained operation is kept below 50 GigaFLOPS of primary computation. · Scalability An indefinite number of Compute Nodes can work together to accomplish computational goals. This scalability is a motivating design requirement of the Compute Node Architecture. · Tera Scale · 1012 FLOPS 25 Compute Nodes are estimated to sustain 1 TeraFLOP using 1,000 CPU Cores. · Peta Scale · 1015 FLOPS 25,000 Compute Nodes are estimated to sustain 1 PetaFLOP using 1,000,000 CPU Cores. · Exa Scale · 1018 FLOPS 25,000,000 Compute Nodes are estimated to sustain 1 ExaFLOP using 1,000,000,000 CPU Cores. Exascale computing is a significant milestone in computer science and engineering. Compute Node Costs · Hardware Compute Node hardware costs less than $1,000. 25 Compute Nodes with 1,500 total CPU Cores cost ~ $15,000 in hardware per availability. · Operation Operating costs are primarily determined by software and hardware engineering labor. Overall Assessment · Summary Overall performance has met high expectations with no technical issues. The architecture has proven to be scalable and adaptive for advanced computational research.
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