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gpuinfo 0.2.0

• Removed the incoming DESCRIPTION spelling NOTE by replacing “loadability” with “shared-library” and shortened the report examples to one scan each.
• Reused command and native probe results within each report to avoid repeated PowerShell launches on Windows. A new report or memory sample observes fresh dynamic values, and temporary observations are discarded even after errors.
• Preserved missing memory for malformed or partly unavailable CUDA process accounting, absent worker rows, and empty sample lists.
• Prevented OS NVIDIA fallback rows from overriding an initialized CUDA driver that reports no visible devices when nvidia-smi is unavailable.
• Corrected has_gpu() so physical-only CUDA devices hidden from the process are not reported as usable process-visible GPUs, while retaining operating- system fallback detection when CUDA provides no device observations.
• Separated successful CUDA driver initialization from device-count query status and exposed driver_device_count_status in cuda_info().
• Made hardware_manifest() reuse one CUDA/device snapshot across its CUDA, NCCL, device, and optional memory sections.
• Added gpu_memory_peak() to combine worker-process samples by GPU UUID and return the highest complete observed memory sum for every expected device. Missing observations remain explicitly unmeasured rather than becoming zero.
• Added cuda_libraries(), a consolidated loadability table for the CUDA driver, CUDA runtime, cuBLAS, cuFFT, cuSOLVER, cuRAND, and NCCL. Optional libraries do not affect has_cuda().
• Added optional nccl_info() inspection that dynamically loads NCCL, queries its version, and reports process-visible CUDA devices without creating a communicator or making NCCL a requirement for CUDA use.
• Added public cpu_info() with physical, logical, and process-available core counts, packages, threads per core, CPU features, and structured provenance.
• Added system_memory_info() with host and effective container RAM, swap, and current-process resident-memory fields in bytes on Linux, macOS, and Windows.
• Extended hardware_info() and hardware_manifest() with host memory and explicit visible/physical GPU counts. Multi-GPU visibility is not presented as evidence that a consuming package can execute across multiple GPUs.
• Added gpu_memory_sample() for timestamped process-level GPU memory samples. CUDA samples are matched by process ID and GPU UUID; Metal samples use MTLDevice.currentAllocatedSize for the current R process.
• Added hardware_manifest() for versioned, serializable benchmark provenance covering the host, devices, generic compute components, and memory.
• Preserved gpu_memory_info() as the backward-compatible device-wide memory snapshot API.
• Added explicit measurement status and reason codes when process memory is unavailable or unsupported, including Windows WDDM limitations.

gpuinfo 0.1.0

• Initial CRAN release with framework-independent CPU, GPU, CUDA, Metal, ROCm, and OpenCL discovery.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.