ThereminQ - CLassiC

Orchestrating Qrack, ELK, Bonsai and Tipsy in OpenCL, VCL and CUDA

ThereminQ orchestrates a suite of best-of-class tools designed to control, extend and visualize data emanating to and from Quantum circuits using Qrack, ELK, Tipsy and Jupyter on CUDA and OpenCL accelerators.

Look also at the following images

Other tags contain

Images can be run independant but are also made to work with the vQbit infrastructure K8s HELM repo

Installation setup and usage scenarios can be glanced at here

Build on CUDA-CLuster stack

and deploy-nvidia-docker WebUI

WebVNC, CUDA 11.4+ & OpenCL 1.2+ with NV, AMD & Intel HW support

Initial vnc password is 00000000

noVNC website is avaliable at port 6080
xRDP running at port 3389 to vnc 127.0.0.1:5900

Docker: deploy an instance of ThereminQ's WebUI controller container

docker run --gpus all \
--privileged \ 
-p 6080:6080 \
--device=/dev/dri:/dev/dri \
--mount type=bind,source=/var/log/qrack,target=/var/log/qrack \
-d twobombs/thereminq:controller

docker run -ti \
--mount type=bind,source=/var/log/qrack,target=/var/log/qrack \
twobombs/thereminq bash /root/run-supreme-cpu

docker run --gpus all \
--device=/dev/dri:/dev/dri \
-ti \
--mount type=bind,source=/var/log/qrack,target=/var/log/qrack twobombs/thereminq bash /root/run-cosmos-gpu1

use --gpus all for NVidia-Docker hosts, in addition --privileged and --device=/dev/dri:/dev/dri will expose all GPUs in the system, eg: AMD/Intel iGPUs

All specialized workloads are listed here

Experimental `bqp=bpp stabilizer_t_nn` high qbit workloads

docker run --gpus all \
--device=/dev/dri:/dev/dri \
-ti \
--mount type=bind,source=/var/log/qrack,target=/var/log/qrack twobombs/thereminq bash /root/run-tnn-gpu1

Archived: Quantum Inspired Qimcifa high qbit workloads ( BigINT OpenCL - Shors' Monte Carlo on 18.04 )

docker run --gpus all \
--device=/dev/dri:/dev/dri \
-d twobombs/thereminq:qimcifa

Tips for Managing high-Qubit and/or high-Node workloads

Workloads with full entanglement and/or Quantum simulations that are at or exceed 30+ Qubits
Mixed workloads based on longer/larger/deeper circuits with partial entanglement that exceed 36+ Qubits

To prevent these workload from taking up all resources of the system it is good to take the following measures

System memory should be at least the amount of RAM where the statevector will fit into
From 30 qubits ( eg: QFT ) count 8GB RAM Memory (and 4 cores with POCL) doubling every additional qubit
Start an instance with a limit for memory and/or swap. eg docker: '-m 16g --memory-swap 32g'
Disable OOM killers in the kernel and/or the container orchestrator ( --oom-kill-disable )
OOM host change: add vm.overcommit_memory = 1 and vm.oom-kill = 0 in /etc/sysctl.conf
Swap should be a dedicated and fast drive where possible NVMe RAID, equal to the bandwith of the GPU/PCIe

Sycamore, QFT & T_NN(-d) Results on an AMD Threadripper 1920X@4.2Ghz

24 Threads with 32GB RAM, 2.5TB NVMe Swap on a 11x RAID NVME drive - Tesla K80 24GB - Tesla M40 24GB results
M40 + K80 run script

If you want to reproduce these results here are some gists to help you along

Note: it is wise to run the benchmarks program inside a main memory limited container with outflow to fast swap so that the system remains stable at intensive runs and high memory peaks - with fast swap we mean FAST NVME RAID0 swap

To run ThereminQ as a VirtualCL controller

note: create the underlying directory structure as mentioned in the VCL readme of Qrackmin

eg:

docker run \
--gpus all \
--device=/dev/dri:/dev/dri \
-d \
--mount type=bind,source=/var/log/vcl,target=/var/log/vcl \
--mount type=bind,source=/var/log/qrack,target=/var/log/qrack twobombs/thereminq:vcl-controller

Questions / Remarks / Ideas / Experiences - In Discord

Code from the following companies and initiatives are in this container

All rights and kudos belong to their respective owners.
If (your) code resides in this container image and you don't want that please let me know.

Code of conduct : Contributor Covenant

BananaPukeh/thereminq