NEWS

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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 (2026-09-26)

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