Next-Gen HPC Architecture

HPC and Linear Algebra as a Service for
Scientific Computing, CAE & AI Workloads

TorsoHPC provides HPCaaS and LAaaS (Linear Algebra as a Service) for large-scale Scientific Computing, CAE, and AI workloads. Define problems locally, execute them on optimized clusters, and reuse data instantly via CAS.

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Architected for Performance. Built for Scale.

Transitioning from local scripts to production-ready remote compute usually requires months of backend engineering. TorsoHPC eliminates that complexity with three core architectural pillars:

Uniquely Universal

One API, Every Backend. TorsoHPC dynamic dispatchers offload kernels to Intel MKL (AVX-512), NVIDIA cuBLAS (CUDA), or AMGCL/Blaze. Using GPU native algorithms and full FP16/32/64 support, we ensure numerical safety while saturating total hardware bandwidth across many architectures.

Uniquely Faster

Eliminate redundant data transfer. Our CAS (Content-Addressable Storage) identifies data by its Intrinsic Mathematical Signature. Upload a 10GB matrix once—reuse it across any session or client instantly.

Uniquely Safer

Every matrix/data upload is secured with AES-GCM 256-bit encryption at rest and in transit. TorsoHPC ensures strict user isolation and provides an audit-ready "Seek-Back" header for metadata without decryption.

Evidence: The Power of CAS

Time saved performing a Sparse Linear Solve (Ax=b) on a 1.2GB Matrix over a 100Mbps link.

Scenario Data Transfer Time to Result
Traditional Remote Execution
Raw Upload + Compute
1,200 MB 112s
TorsoHPC (Initial Run)
Encrypted V3 Stream + Compute
1,200 MB 84s
TorsoHPC (Repeat Solve)
CAS Cache Hit + Compute
0 MB 12s (89% Faster)

Tested on AMD Ryzen 7 PRO / NVIDIA A100 Backend.

Golden Workflows

Optimized pipelines for engineering and AI.

Engineering

Parametric Sweeps

Upload your stiffness matrix once. Solve against 500 different load vectors without re-transferring the geometry data.

AI Inference

Large Model Prototyping

Offload heavy GEMM/GEMV primitives to remote GPU nodes while maintaining a clean Python-based development loop.

Integration

Native Automation

Inject remote compute directly into existing scientific codebases via the torso_client.hpp native C++ header.

Flexible Deployment

TorsoHPC fits into your security model, not the other way around.

SaaS (Shared Cluster)

Get started in seconds. Secure multi-tenant access to our global GPU/MKL nodes.

Private VPC

Deploy TorsoHPC inside your AWS/GCP/Azure subnet for zero-latency VPC peering.

On-Prem / Air-Gapped

Complete sovereignty. Run the Compute Server on your own HPC hardware with no external link.

Simplistic Pricing Structure

TorsoHPC offers a flat, transparent pricing model to keep your experience positive and predictable.

Pay-As-You-Go

You only pay for what you use.

  • No Monthly Minimums: Scale up or down as your project requires.
  • Compute-Second Billing: Precise tracking of MKL and CUDA execution time.
  • Storage Tiering: Cost-optimized rates for LOCAL/NFS vs performance-optimized VRAM.
  • Infinite Scaling: Pay for additional VM nodes only when they are active.
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Operational Architecture

A transparent, high-performance pipeline with real-time encrypted streaming.

Encrypted V3 Streaming Pipeline High-Speed Execution Verify Identity Reusable O(1) CAS cache Edge Clients CLI | Python | WASM Compute Server C++ V3 Protocol Hub Content Registry Mathematical CAS Solver Backends BLAS | CUBLAS | MKL | BLAZE | AMGCL