






maxNofExtended property, which provides an upper-bound estimate of the maximum number of results that can be generated from a selected synthon during extension steps.For older versions and the full changelog, please click here.
C-S-D in the GUI and API flavors runs its calculations on HPSee. HPSee works as a set of services: a database, an API and workers that carry out the calculations. The hardware you need depends on how you deploy HPSee: on one machine, on a cluster or on AWS.
Each setup has its own hardware requirements. Answer up to three questions to find yours.
| Question | Your answer | Your setup |
| 1. Where do you want to run HPSee? | On premises | Continue with question 2 |
| On AWS | AWS | |
| 2. How is your on-premises hardware organized? | A cluster controlled by a scheduling system, such as Slurm | Small or large cluster, run with Apptainer or a hybrid of Docker and Apptainer |
| Machines dedicated to HPSee | Continue with question 3 | |
| 3. How many machines do you dedicate to HPSee? | One machine | Single machine, run with Docker Compose or Apptainer |
| Several machines | Small or large cluster, run with Docker Swarm or Apptainer |
Small and large clusters differ in the number of worker nodes. The worker requirements in the last row apply to every setup.
| Setup | Single machine | Small cluster | Large cluster | AWS |
| How HPSee runs | One machine used only by HPSee, with all services on it | Docker Swarm or Slurm orchestration with a dedicated manager node | Docker Swarm or Slurm orchestration with a dedicated manager node | Managed cluster |
| Worker nodes | 1 | 10–20 | 150 | Up to 300 |
| Database | Container on the same machine | On the manager node | On the manager node | Amazon Aurora PostgreSQL |
| Manager node | No separate manager node | 8 vCPU and 16 GB RAM, plus the database host (see below) | 16 vCPU and 32 GB RAM, plus the database host (see below) | 16 vCPU and 32 GB RAM, plus the database |
| Worker, per job | 8 vCPU, 8 GB RAM (16 GB recommended) and at least 10 GB of disk space (20 GB NVMe recommended). To run several jobs on one worker node, multiply CPU and RAM by the number of jobs. | |||
Example: sizing a single machine (Compose Mode)
On a single machine, the database, the API and the worker share the hardware, so their requirements add up. This example uses the recommended values where available.
| Resource | Database | API | Worker (1 job) | Total |
| CPU | 8+ cores | 4 vCPU | 8 vCPU | 20+ vCPU |
| RAM | 32 GB | 8 GB | 16 GB | 56 GB |
| Database container memory budget | 16 GB | Not applicable | Not applicable | 16 GB, included in the RAM total |
| Disk | 500 GB+ NVMe | 100 GB+ | 20 GB NVMe | 620 GB+ |
| Network | Not applicable (loopback) | 10 GbE if users download whole libraries | 1 GbE | 1 GbE, or 10 GbE if users download whole libraries |
HPSee runs as separate services. Docker Compose and Docker Swarm setups run the API, the database and at least one worker. Slurm setups also run the EventBroker. In cluster setups, the API and the EventBroker run as one replica each on the manager node, which also hosts the database. Only the number of workers changes with the size of the setup. Each cell lists the minimum first and the recommended value below it.
| Database host | Single machine | Small cluster | Large cluster |
| CPU | 8 vCPU Recommended: 8+ cores |
8 vCPU Recommended: 16 vCPU |
16 vCPU Recommended: 32 vCPU |
| Host RAM | 16 GB Recommended: 32 GB |
32 GB Recommended: 64 GB |
96 GB Recommended: 128–192 GB |
| Container memory budget* | 8 GB Recommended: 16 GB |
24 GB Recommended: 48 GB |
80 GB Recommended: 128 GB |
| Disk | 250 GB NVMe Recommended: 500 GB+ |
1 TB NVMe, ≥ 500 MB/s, ≥ 5,000 IOPS Recommended: 2 TB, ≥ 1 GB/s |
2 TB NVMe, ≥ 1 GB/s, ≥ 20,000 IOPS Recommended: 4 TB, separate WAL (write-ahead log) volume |
| Network | Not applicable (loopback) | 1 GbE Recommended: 10 GbE |
10 GbE, required |
* From HPSee 3.0, the installer asks for the container memory budget.
| Resource | API | EventBroker | Worker (per job) |
| CPU | 2 vCPU Recommended: 4 vCPU |
1 vCPU | 8 vCPU |
| RAM | 4 GB Recommended: 8 GB |
512 MB Recommended: 1 GB |
8 GB Recommended: 16 GB |
| Disk (/datastorage) | At least 20 GB Recommended: 100 GB+ |
Image only, about 1 GB Recommended: 5 GB with log headroom |
1 GB per concurrent job, at least 10 GB Recommended: 20 GB NVMe |
| Network | 1 GbE Recommended: 10 GbE if users download whole libraries |
Shared | 1 GbE Recommended: 10 GbE at 100+ nodes |
Worker values apply to one job. To run several jobs on one worker node, multiply CPU and RAM by the number of jobs per node. Disk and network requirements stay the same.
| Category | Requirement | Details |
| HPSee server: operating systems | ||
| Linux | Supported | Docker Engine or Apptainer, depending on your setup |
| Windows | Supported | Windows 10 (version 1903, build 18362) or later, with WSL2 and Docker Desktop |
| macOS | Not currently supported | HPSee server installations are not currently supported on macOS |
| SeeSAR client | ||
| Memory (RAM) | 16 GB | Required for working with C-S-D results in SeeSAR |
| Operating systems | Fully supported | Linux, macOS and Windows |
Note: All hardware requirements are intended as guidance. Actual needs depend on your workload, for example the number of jobs that run at the same time. Setups on dedicated machines need hardware reserved for HPSee, because HPSee does not throttle itself for other jobs on the same machine. The deployment options available to you depend on your HPSee version. The HPSee Deployment Guide describes the installation for each setup. We refine these requirements continuously as HPSee evolves and as we gain experience from more deployments, so values may be updated over time.
Benchmark: In an internal benchmark on protein kinase A (PKA) in Enamine’s REAL Space (7.6 × 1010 compounds at the time of testing) using SeeSAR 14.1.1 and HPSee 2.1.1, anchoring required 9.3 hours of computation time, followed by extension steps of 30.8 hours (100 fragments) and 9.2 hours (50 fragments), on 9 computers with 16 cores and 64 GB RAM each. Actual runtimes vary with the target, Chemical Space, C-S-D settings and available hardware.

