AI infrastructure is becoming a stack, not a box
Open rack, networking and software standards reduce vendor lock-in. gigaRAM is the memory layer inside that stack.
Open AI infrastructure
Two routes
One stack, two architectures
Vertically integrated stack
Open infrastructure
NVIDIA remains the benchmark for highly integrated AI infrastructure. The open route is developing alongside it — a second path, not a replacement.
OCP Open Rack Wide
ORW in plain terms
A standard, not a product
ORW is an open AI rack specification within the Open Compute Project. It is not an accelerator, not an AMD product and not a new class of GPU.
One architecture, many vendors
Servers, accelerators, networking, storage, power and liquid cooling are designed to a shared form factor and stay compatible with each other.
AMD Helios is one example
The AMD Helios rack system with MI400 / MI455X-generation accelerators is one implementation of this approach. An important one — not the only one.
One rack, several suppliers
OCP ORWThe open standard defines mechanics, power and cooling. Who supplies each component is the customer's decision.
The Open AI Software Stack
The open software stack
ORW itself does not define the software stack. Its significance lies elsewhere: hardware infrastructure becomes more standardized and open, while software is increasingly built around Linux and the open-source ecosystem.
Where gigaRAM sits
A memory layer, not another AI framework
gigaRAM sits between AI workloads and a server's physical memory, intelligently distributing data across DRAM and NVMe.
Open compute needs open memory infrastructure.
- Transparent to applications
- Linux-native
- Hardware-independent approach
- Designed for open infrastructure
- Reduces dependence on expensive DRAM
- Enables larger workloads on existing servers
- Suitable for AI, databases and memory-intensive applications
gigaRAM does not replace accelerator HBM and is not part of ORW or Helios. It is a separate software infrastructure layer that can complement open AI infrastructure.
Measured on real workloads
Redis: 48 vCPU, 50M keys at 16 KiB. PostgreSQL is a deliberately conservative projection. Both are verified by a pilot on your own workload.
Comparison
A trade-off, not a winner
Vertically Integrated
- One vendor
- GPU
- Interconnect
- Networking
- Software ecosystem
Maximum integration and a mature ecosystem.
Open Infrastructure
- Multiple vendors
- Open rack standards
- Open networking / interconnect standards
- Linux
- Open-source AI software
- Independent infrastructure software
Flexibility, supplier choice and room for independent infrastructure software.
Neither approach is universally right. The choice depends on timelines, scale, team skills and procurement strategy.
Trend 2027+
AI infrastructure is becoming a stack, not a box.
The next phase of the market is not only a GPU race. Competition moves up to the level of the whole AI factory.
As open standards spread, space opens up for independent companies that build the best component of each layer.
The future of AI infrastructure will not be defined by compute alone.
gigaRAM is building the intelligent memory layer for that future.
In short
Frequently asked questions
What is OCP Open Rack Wide (ORW)?
An open AI rack standard developed within the Open Compute Project. It defines mechanics, power, cooling and hardware integration, so different manufacturers can build compatible servers, accelerators, networking and storage.
Is ORW an AMD product or a new type of GPU?
No. ORW is an open rack specification — neither a specific vendor's product nor a class of accelerator. Any hardware manufacturer can build to it.
How do AMD Helios and MI400 / MI455X relate to it?
AMD Helios is a rack-scale AI system built on open rack architecture principles, using MI400 / MI455X-generation accelerators. It is an important example of the approach — not the standard itself.
Does ORW define the software stack?
No. ORW standardizes hardware infrastructure. Software is increasingly built around Linux and the open-source ecosystem: ROCm and other open accelerator layers, PyTorch and JAX, vLLM and SGLang, Kubernetes and Slurm.
Where does gigaRAM sit in this stack?
gigaRAM is a memory infrastructure layer between AI workloads and a server's physical memory. It transparently distributes data across DRAM and NVMe, letting larger workloads run on existing servers. It is not part of ORW or Helios and does not replace accelerator HBM.