gpuInfo — Return a formatted status string that describes the active GPU provider.

gpuInfo() returns a concise, human-readable string that summarises the active GPU acceleration provider. It is a convenience wrapper around gpuDevice, intended for logging or displaying status information in the REPL and notebooks.

How gpuInfo works

• Queries the same device metadata as gpuDevice() and formats the fields into GPU[key=value, ...].
• Includes identifiers (device_id, index), descriptive strings (name, vendor, backend) and capability hints (precision, supports_double, memory_bytes when available).
• Escapes string values using MATLAB-style single quote doubling so they are display-friendly.
• When no acceleration provider is registered, returns the placeholder string GPU[no provider] instead of throwing an error, making it safe to call unconditionally.
• Propagates unexpected errors (for example, if a provider fails while reporting metadata) so they can be diagnosed.

GPU memory and residency

gpuInfo is a pure metadata query and never changes residency. Arrays stay wherever they already live (GPU or CPU). Use gpuArray, gather, or RunMat Accelerate's auto-offload heuristics to move data between devices as needed.

Examples

Displaying GPU status in the REPL

disp(gpuInfo())

Expected output:

GPU[device_id=0, index=1, name='InProcess', vendor='RunMat', backend='inprocess', precision='double', supports_double=true]

Emitting a log line before a computation

fprintf("Running on %s\n", gpuInfo())

Expected output:

Running on GPU[device_id=0, index=1, name='InProcess', vendor='RunMat', backend='inprocess', precision='double', supports_double=true]

Checking for double precision support quickly

summary = gpuInfo();
if contains(summary, "supports_double=true")
    disp("Double precision kernels available.");
else
    disp("Falling back to single precision.");
end

Handling missing providers gracefully

% Safe even when acceleration is disabled
status = gpuInfo();
if status == "GPU[no provider]"
    warning("GPU acceleration is currently disabled.");
end

Combining gpuInfo with gpuDevice for structured data

info = gpuDevice();
summary = gpuInfo();
if isfield(info, 'memory_bytes')
    fprintf("%s (memory: %.2f GB)\n", summary, info.memory_bytes / 1e9);
else
    fprintf("%s (memory: unknown)\n", summary);
end

Expected output:

GPU[device_id=0, index=1, name='InProcess', vendor='RunMat', backend='inprocess', precision='double', supports_double=true] (memory: 15.99 GB)

FAQ

Related Acceleration functions

Open-source implementation

Unlike proprietary runtimes, every RunMat function is open-source. Read exactly how gpuInfo works, line by line, in Rust.

• View gpuInfo.rs on GitHub
• Learn how the runtime works
• Found a bug? Open an issue with a minimal reproduction.

About RunMat

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• Simulations that took hours now take minutes. RunMat automatically optimizes your math for GPU execution on Apple, Nvidia, and AMD hardware. No code changes needed.
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