GPU computing
CUDA, HIP and SYCL kernels for simulation, analytics, signal processing and ML inference.
Engineering studio · GPU · C++ · Systems
Software that runs at the speed of parallel.
ComputeIT designs and builds GPU-accelerated, low-latency systems. We turn slow, sequential workloads into fast, reliable, production-grade platforms — from the CUDA kernel up to the cluster architecture.
0years of engineering experience
0GPU & HPC projects delivered
0uptime on production platforms
0best speed-up over baseline CPU code
Capabilities
Deep engineering across the whole stack
Most performance problems are not solved at one layer. We work from silicon to service boundary, so the fixes hold up in production.
Modern C++
Clean, testable C++20/23 with zero-cost abstractions, lock-free structures and cache-friendly memory layouts.
System design
Architectures that scale and degrade gracefully, documented before the first line ships.
Performance engineering
Profile-driven optimization with Nsight and perf, plus benchmark gates in CI so regressions never sneak back in.
Scientific & numerical
Solvers, Monte Carlo, FFTs and sparse linear algebra — numerically stable and reproducible.
Reliability & tooling
Sanitizers, fuzzing, observability and build systems — fast code also has to be correct and maintainable.
Code
The kind of code we write every day
Small, sharp and explicit about the hardware: shared-memory tiling, cache-line aware lock-free queues and overlapped copy/compute pipelines.
System design
A reference architecture for GPU services
A typical compute platform we design. Select a stage to see the decisions behind it.
Design considerations
Results
Outcomes engineers care about
Representative engagement results across finance, simulation and media processing.
0
Risk simulation
Monte Carlo pricing engine moved from a CPU farm to multi-GPU nodes. Overnight batch became an interactive, on-demand query.
- CUDA
- NCCL
- C++20
0
Market-data path
Lock-free, allocation-free ingest pipeline with cache-aligned queues and kernel-bypass networking. p99 tail latency cut by 9×.
- Lock-free
- DPDK
- perf
0events/s per node
Video analytics platform
Batching scheduler and CUDA-graph workers keep GPUs above 90% utilization while honouring per-tenant latency SLOs.
- gRPC
- TensorRT
- Kubernetes
Contact
Have a workload that's too slow?
Tell us about it. You'll hear back from an engineer — not a sales team — within one business day.
- Emailhello@computeit.sk
- EngagementsAudits · Prototypes · Embedded teams · Long-term platform work
- TimezoneRemote-first, overlapping EU & US hours