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AMD uProf supersedes CodeAnalyst and CodeXL for CPU and Power profiling on AMD processors. GUI based code profiler; does only basic timer-based profiling on Intel processors. Based on OProfile. Free/open source (GPL) or proprietary AMD CodeXL by AMD: Linux, Windows For GPU profiling and debugging: OpenCL.
Argus Monitor: Windows: Trialware [3] GUI IDE(PATA), SATA eSATA, USB Some RAID controllers Yes ? By window, sound, email, program execution at choosable parameter changes, threshold Also shows temperature of CPU, GPU, CPU core speed, Intel Turbo Boost status, CPU power consumption, system load and system fan speeds. Can control speed of GPU and ...
CodeXL's GPU profiler collects and visualizes hardware performance counters data, application trace, kernel occupancy, and offers hotspot analysis for AMD GPUs and APUs. . The profiler gathers data from the OpenCL runtime, and from the GPU/APU itself during the execution of the kernels, and can be used to discover performance bottlenecks and optimize kernel execut
CPU-Z is more comprehensive in virtually all areas compared to the tools provided in the Windows to identify various hardware components, and thus assists in identifying certain components without the need of opening the case; particularly the core revision and RAM clock rate. It also provides information on the system's GPU.
RivaTuner is a freeware overclocking and hardware monitoring program that was first developed by Alexey Nicolaychuk in 1997 [1] for the Nvidia video cards.It was a pioneering application that influenced (and in some cases was integrated into) the design of subsequent freeware graphics card overclocking and monitoring utilities.
TechPowerUp GPU-Z (or just GPU-Z) is a lightweight utility designed to provide information about video cards and GPUs. [2] The program displays the specifications of Graphics Processing Unit (often shortened to GPU) and its memory; also displays temperature, core frequency, memory frequency, GPU load and fan speeds.
Ganglia is a scalable, distributed monitoring tool for high-performance computing systems, clusters and networks. The software is used to view either live or recorded statistics covering metrics such as CPU load averages or network utilization for many nodes.
The number of available hardware counters in a processor is limited while each CPU model might have a lot of different events that a developer might like to measure. Each counter can be programmed with the index of an event type to be monitored, like a L1 cache miss or a branch misprediction.