![]() It is also a requirement for 100 Gbps egress bandwidth. gVNIC is a new device driver and tightly integrates with Google’s Andromeda virtual network stack to help achieve higher throughput and lower latency. We also changed the network driver from virtio to the new Google Virtual NIC (gVNIC). This increase was a big factor that made this 100-trillion experiment possible, allowing us to move 82.0 PB of data for the calculation, up from 19.1 PB in 2019. Back in 2019 when we did our 31.4-trillion digit calculation, egress throughput was only 16 Gbps, meaning that bandwidth has increased by 600% in just three years. The n2-highmem-128 machine type’s support for up to 100 Gbps of egress throughput was also critical. This VM shape is part of the most popular general purpose VM family in Google Cloud. It satisfied our requirements: high-performance CPU, large memory, and 100 Gbps egress bandwidth. The amount of available memory and network bandwidth were the two most important factors, so we selected n2-highmem-128 (Intel Xeon, 128 vCPUs and 864 GB RAM). ![]() Choosing the right machine type for the jobĬompute Engine offers machine types that support compute- and I/O-intensive workloads. The scripts we used are available on GitHub if you want to look at the actual code that we used to calculate the 100 trillion digits. In other words, the calculation could’ve taken 300 days instead of 157 days! Overall, the final design for this calculation was about twice as fast as our first design. We also developed a small program that runs y-cruncher with different parameters and automated a significant portion of the measurement. Terraform helped us test dozens of different infrastructure options in a short time. ![]() ![]() There are also a number of combinations of parameters in the operating system, infrastructure, and application itself. We knew the calculation would run for several months and even a small performance difference could change the runtime by days or possibly weeks. In this way, we were able to recreate the entire cluster with just a few commands. Part of the guest OS setup process was handled by startup scripts. The Terraform scripts created OS guest policies to help ensure that the required software packages were automatically installed. We also wrote a couple of shell scripts to automate critical tasks such as deleting old snapshots, and restarting from snapshots (we didn’t need to use this though). We used Terraform to set up and manage the cluster. The N2 machine series provides balanced price/performance, and when configured with 16 vCPUs it provides a network bandwidth of 32 Gbps, with an option to use the latest Intel Ice Lake CPU platform, which makes it a good choice for high-performance storage servers. The higher bandwidth support is a critical requirement for the system as we adopted a network-based shared storage architecture.Įach storage server is a n2-highcpu-16 machine configured with two 10,359 GB zonal balanced persistent disks. The main compute node is a n2-highmem-128 machine running Debian Linux 11, with 128 vCPUs and 864 GB of memory, and 100 Gbps egress bandwidth support. Total I/O: 43.5 PB read, 38.5 PB written, 82 PB total. ![]() Total storage size: 663 TB available, 515 TB used.Total elapsed time: 157 days, 23 hours, 31 minutes and 7.651 seconds.Compute node: n2-highmem-128 with 128 vCPUs and 864 GB RAM.Program: y-cruncher v0.7.8, by Alexander J.It’s a long list, but we’ll explain each feature one by one.īefore we dive into the tech, here’s an overview of the job we ran to calculate our 100 trillion digits of π. The underlying technology that made this possible is Compute Engine, Google Cloud’s secure and customizable compute service, and its several recent additions and improvements: the Compute Engine N2 machine family, 100 Gbps egress bandwidth, Google Virtual NIC, and balanced Persistent Disks. This achievement is a testament to how much faster Google Cloud infrastructure gets, year in, year out. This is the second time we’ve used Google Cloud to calculate a record number 1 of digits for the mathematical constant, tripling the number of digits in just three years. Today we’re announcing yet another record: 100 trillion digits of π. Then, in 2021, scientists at the University of Applied Sciences of the Grisons calculated another 31.4 trillion digits of the constant, bringing the total up to 62.8 trillion decimal places. In 2019, we calculated 31.4 trillion digits of π - a world record at the time. ![]()
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