Industries/ AI, Data & Compute/ Scientific Computing

Scientific Computing on PYRAX

Scientific computing powers simulation, genomics, climate modeling, and drug discovery — HPC workloads that are compute-starved, expensive, and increasingly demand reproducibility and secure collaboration on sensitive data. PYRAX opens supercomputer-class capacity through PYRAX Compute's pooled GPUs and ShardedExecutor, binds every run to a ComputeReceipt for reproducibility, and uses compute-to-data so institutions can jointly analyze private cohorts without ever sharing the raw data.

Market size
$54B (2024)
Projection
$132B by 2032 · ~11% CAGR

The market

$54B
HPC market (2024)
$2.75T
Global R&D spend
~50%
Studies failing reproducibility
months
Research idle to compute waitlists

Source: MarketsandMarkets, 2024. Figures are indicative and provided for context.

What's broken today

Access to HPC clusters is gated by grants, queues, and institutional allocation.
Published results are often not reproducible because the exact code, data, and environment are lost.
Cross-institution collaboration on sensitive data (patient genomes, proprietary compounds) is blocked by privacy law.
Grant and compute spending is hard to audit and attribute to specific runs.

How PYRAX transforms it

Concrete network elements mapped to this business.

PYRAX Compute pooled HPC + ShardedExecutor

Large simulations shard across cohorts of consumer and datacenter GPUs, giving labs elastic, supercomputer-class capacity billed at 8 PYRX/CU without a cluster allocation.

ComputeReceipt reproducibility

Each run emits a receipt pinning the code, inputs, seeds, and environment, so a result can be independently re-executed and verified — the missing link for reproducible science.

Compute-to-data collaboration

Institutions run shared models against each other's private datasets in place, enabling federated genomics or multi-site trials with no raw data ever leaving its owner.

Content-addressed data & code

Datasets, containers, and analysis code are addressed by hash, giving every paper an immutable, citable, verifiable computational artifact.

Escrow-metered grant spend

Grant funds escrow per job and release against verified receipts, producing a transparent, auditable trail of exactly what compute each result cost.

Buildathon: dApp ideas

Ship-ready concepts for scientific computing on PYRAX.

SimGrid

01

Elastic HPC broker that shards simulations across pooled GPUs and bills per verified CU.

ComputeScheduler

ReproPaper

02

Reproducibility registry pairing each publication with a ComputeReceipt and content-addressed artifact.

ComputeReceiptStorage

FedGenome

03

Federated genomics platform that runs models across hospitals' private cohorts via compute-to-data.

Compute-to-dataShielded

GrantLedger

04

Grant-management dApp that escrows funds per run and produces an auditable compute-spend trail.

EscrowGov

MolSearch

05

Distributed drug-discovery screen that fans docking jobs across the PYRAX Compute pool.

ComputeScheduler

ClimateProof

06

Climate-model runner that publishes ZK-verifiable results others can trust without re-running.

ZKComputeReceipt

PeerCompute

07

Idle-cluster sharing network where research groups trade unused GPU-hours peer-to-peer.

ComputeEscrow

DataCite

08

Content-addressed dataset citation service giving every corpus an immutable, verifiable reference.

StorageEVM