Game performance optimisation

You might be chasing the last few milliseconds before a milestone, investigating a spike that only happens in a busy scene, or bringing a game to hardware with a tighter budget. Meanwhile, your engine team still has a production roadmap to deliver.

We take on a focused performance investigation and the implementation that follows. Bring a representative build, target hardware and the constraint you need to resolve. Together we establish a baseline and agree where the work will have the most value for your project.

Gameplay, animation, physics, visibility and render submission all compete for CPU time. We profile the main thread and worker jobs, then work on the data layout, cache behaviour, allocations and algorithms behind the expensive paths. SIMD vectorisation, intrinsics and ISPC can help with suitable data-parallel workloads, with instruction-set support and fallback paths matched to your target CPUs.

Multithreading also needs the right shape of work. We tune job granularity, dependencies, work distribution and synchronisation, investigating lock contention, false sharing and idle workers. The goal is a shorter frame-critical path and predictable behaviour under load, with correctness and memory use checked alongside the timings.

Loading and streaming cross several systems. We trace disk access, decompression, deserialisation and GPU upload together, then address asset layout, request batching, caching, asynchronous I/O and back-pressure. DirectStorage integration and decompression paths can be part of that work on supported targets, with appropriate storage paths for the rest of your platform set.

Network performance belongs in the same investigation. We work on serialisation, payload size, request batching, update frequency and download or streaming behaviour, measuring bandwidth, latency and jitter against the game’s needs. Queueing, retries and CPU-side processing can matter as much as raw disk or network throughput.

A long GPU event can be the symptom of a dependency elsewhere in the frame. We follow the cost through CPU submission, queue synchronisation, shader execution, data movement and resource lifetime, using captures from the workload that matters to your game.

The outcome is a change in your codebase. That may mean restructuring passes, reducing memory traffic, changing an acceleration-structure strategy, or moving repeated work into asset preparation and streaming. We keep the investigation small enough to compare and the implementation grounded in your engine’s constraints.

We measure the changed build against the same conditions, including image quality and memory use. Your team can see what improved, what trade-off was made, and which bottleneck now sets the limit.

Your technical leads work directly with the engineers doing the investigation. We use your source control, build infrastructure and review process, and agree the scope with the people responsible for the game’s performance and visual direction.

Our rendering and GPU research gives us experience below the engine boundary as well as inside it. That helps when a workload behaves differently across vendors or an API feature needs careful integration. The collaborations below show that experience in practice.