About Technova
Technova Information Ltd is a heterogeneous GPU compute provider registered in Glasgow, Scotland. We serve customers across the United Kingdom, Europe and the United States from data centres in Glasgow, London and Texas. We are skilled in both NVIDIA CUDA and AMD ROCm, with our core differentiation being full-stack ROCm optimisation and CUDA→ROCm migration services. We deliver physically exclusive, strictly isolated GPU compute with manual deployment by our engineering team. No self-service cloud console — every resource is deployed and configured by our technical team.
Data Centre Infrastructure
Our compute, storage and networking equipment resides across three data centres — Glasgow (HQ) and London in the UK, and Texas in the US — serving customers in the United Kingdom, Europe and the United States. All sites feature industry-leading PUE values, 400G NDR InfiniBand fabric, and physically exclusive GPU instances. UK customer data stays in the UK for sovereignty; US workloads are served from Texas.
Core Technical Capabilities
Dual-Stack CUDA + ROCm
Professional full-stack expertise across both NVIDIA CUDA and AMD ROCm ecosystems — from custom GEMM/Attention/MoE kernels up to distributed training and inference serving.
400G IB Cluster Operation
Spine-leaf topology, full bisection bandwidth, distributed-training ready across 400G NDR InfiniBand and 800G RoCE v2 fabrics.
End-to-End Migration Services
CUDA→ROCm migration, operator adaptation, VRAM tuning and distributed training acceleration — plus a drop-in vLLM-ROCm serving stack with up to 2× higher throughput on AMD MI300X.
The full-stack AMD GPU platform — from custom kernels to serving
Unlike general GPU rental providers, Technova delivers professional-grade AMD ROCm full-stack optimisation. We cover the entire stack across AMD Instinct accelerators — from chip-level kernels to cluster-level serving — drastically reducing enterprise migration cost and unlocking peak inference and training performance on AMD silicon.
Custom AMD kernels
GEMM, Attention and MoE kernels tuned for MI300X / MI350X CDNA memory hierarchy and matrix engines — for training and inference workloads that demand peak hardware utilisation.
Drop-in vLLM-ROCm
A drop-in replacement for upstream ROCm vLLM with up to 2× higher throughput on AMD GPUs — optimised scheduling, paged KV-cache and quantisation for DeepSeek, Llama, Qwen and custom models.
Heterogeneous inference
Unify NVIDIA and AMD GPUs across vendors, architectures and generations into a single inference cluster — prefill on H200, decode on MI300X, with cross-vendor prefill/decode disaggregation.
Inference cost optimisation
Maximise tokens per dollar through chip-level kernel tuning, communication optimisation, prefix-cache-aware routing and multi-vendor infrastructure utilisation.
CUDA→ROCm migration
Full-lifecycle model migration from CUDA to ROCm — operator adaptation, VRAM tuning, RCCL collective tuning and distributed-training acceleration, with a measured regression test plan.
End-to-end inference stack
Routing, scheduling, autoscaling, SLO-driven optimisation and KV-cache management — a production-grade serving stack that runs unmodified on AMD MI300X / MI350X clusters.
Technova Information Ltd
Tay House, 300 Bath Street, Glasgow, Scotland, G2 4JR, United Kingdom
Company No. SC822077