System optimization#
2024-07-16
5 min read time
System administrators can optimize the performance of their AMD hardware generally and based on specific workloads and use cases. This section outlines recommended system optimization options for AMD accelerators and GPUs, enabling administrators to maximize efficiency and performance.
High-performance computing workloads#
High-performance computing (HPC) workloads have unique requirements that may not be fully met by the default hardware and BIOS configurations of OEM platforms. To achieve optimal performance for HPC workloads, it is crucial to adjust settings at both the platform and workload levels.
The AMD Instinct™ accelerator optimization guides in this section describe:
BIOS settings that can impact performance
Hardware configuration best practices
Supported versions of operating systems
Workload-specific recommendations for optimal BIOS and operating system settings
The guides might also discuss the AMD Instinct software development environment, including information on how to install and run the DGEMM, STREAM, HPCG, and HPL benchmarks. The guides provide a good starting point but is not tested exhaustively across all compilers.
Knowledge prerequisites to better understand the following Instinct system optimization guides and to perform tuning for HPC applications include:
Experience in configuring servers
Administrative access to the server’s Management Interface (BMC)
Administrative access to the operating system
Familiarity with the OEM server’s BMC (strongly recommended)
Familiarity with the OS specific tools for configuration, monitoring, and troubleshooting (strongly recommended)
While the following guides are a good starting point, developers are encouraged to perform their own performance testing for additional tuning per device and per workload.
Optimization guide |
Architecture reference |
White papers |
|---|---|---|
Workstation workloads#
Workstation workloads, much like those for HPC, have a unique set of requirements: a blend of both graphics and compute, certification, stability and others.
The document covers specific software requirements and processes needed to use these GPUs for Single Root I/O Virtualization (SR-IOV) and machine learning tasks.
The main purpose of this document is to help users utilize the RDNA™ 2 GPUs to their full potential.
Optimization guide |
Architecture reference |
White papers |
|---|---|---|