Fiery

I meant to write RAID or AHCI

CPU#1 is the CPU Diode temperature sensor. DIMM temperature sensing has to be activate in AIDA64 / main menu / File / Preferences / Stability, by enabling DIMM TS sensor support. You need to restart AIDA64 after altering that option. North Bridge temperature should be correct. You can compare the measured value against Gigabyte EasyTune to verify.

In case you can only see 2 temperature readings in the BIOS Setup's H/W Monitor or PC Health Status screen, and Gigabyte's own EasyTune utility also shows only 2 temperature readings, then it's safe to assume your motherboard is only capable of measuring those 2 temperatures. The third one could be anything, even a bogus value. Regards, Fiery

Thank you for the data. What exactly is the problem with the sensor readings?

Thank you for the feedback. Please note that AIDA64 uses standard synchronization mutexes to synchronize its low-level hardware access functions with other software. AFAIK SpeedFan uses the same mutexes (so as CPU-Z, HWiNFO, HWMonitor, SIV, etc), but maybe it isn't implemented there properly

Thank you for the sensor dump. It looks like AIDA64 has difficulties reading motherboard temperature on your board. Somehow the sensor chip doesn't provide a stable and reliable motherboard temperature reading. It could be because the low-level sensor module of AIDA64 collides with another monitoring application. Do you have any such applications installed, either made by MSI or another company? Thanks, Fiery

On modern AMD processors the core temperature diode may provide incorrect, very low readings when the processor is idle. When we've asked AMD about this, they said that the diode will only provide reliable readings when the CPU is under load. It's a hardware issue that we cannot fix from AIDA64. As for the HDD issue, that usually happens when you have multiple drives connected to an AMD SATA controller configured as RAID controller. AMD's RAID drivers do not provide the necessary ATA passthrough interface to access all drives of the RAID array, but instead it only allows access to the first drive. Regards, Fiery

Those spikes could be because of unstable measurement of APIC clock -- which equals to BCLK on Sandy Bridge, Ivy Bridge and Haswell. Please let me know what motherboard do you have, what operating system do you have installed, and which software do you use to encode video, and we'll try to reproduce the issue on our test systems. Thanks, Fiery

On Intel GPUs GPU-Z measures GPU utilization via Direct3D calls. Such Direct3D calls are not used by AIDA64 simply because they aren't fully reliable. Limitation #1: they only measure Direct3D load, and not the actual GPU load. Hence, if you start a computing task (via OpenCL), the Direct3D "GPU utilization" value will not show the actual GPU utilization, but a much lower value. Limitation #2: those Direct3D calls only works properly on single-GPU systems, due to the fact that Direct3D doesn't properly support multiple GPU devices. Regards, Fiery

Fixed. Thank you for noticing.

We're rolling out a new major update to AIDA64 in a few weeks. It will feature the usual improvements to support the latest and greatest hardware technologies, such as GPU details for AMD Radeon R5, R7 and R9 Series and nVIDIA GeForce GTX 760 Ti OEM, and optimized benchmarks for AMD Kaveri and Intel Bay Trail. But most importantly, we're introducing a brand new benchmark panel that offers a set of OpenCL GPGPU benchmarks that you can launch from AIDA64 / main menu / Tools / GPGPU Benchmarks. These benchmarks are designed to measure GPGPU computing performance via different OpenCL workloads. Every benchmark methods are designed to work on up to 16 GPUs, including AMD, Intel and nVIDIA GPUs, in any combination. Of course CrossFire and SLI configurations, and both dGPUs and APUs are also fully supported. HSA configurations are handled via preliminary support. Basically any computing capable device will be benchmarked that appears as a GPU device among OpenCL devices. The OpenCL benchmark methods currently offered are not specifically optimized for any GPU architectures. Instead, the AIDA64 OpenCL module relies on the OpenCL compiler to optimize the OpenCL kernel to run best on the underlying hardware. The OpenCL kernels used for these benchmarks are compiled in real-time, using the actual OpenCL driver the OpenCL GPU device belongs to. Due to that approach, it is always best to have all video drivers (Catalyst, ForceWare, HD Graphics, etc) updated to their latest & greatest version. For compilation the following OpenCL compiler options are passed: -cl-fast-relaxed-math -cl-mad-enable. On top of that, the GPGPU Benchmark Panel also has a CPU column, for comparison purposes. The CPU measurements however are not obtained via OpenCL, but using native x86/x64 machine code, utilizing available instruction set extensions like SSE, AVX, AVX2, FMA and XOP. The CPU benchmarks are very similar to the old CPU and FPU benchmarks AIDA64 has got, but this time they measure maximum computing rates (FLOPS, IOPS). The CPU benchmarks are heavily multi-threaded, and are optimized for every CPU architectures introduced since the first Pentium came out. The following benchmark methods are currently offered. We've indicated the x86/x64 CPU benchmark difference in brackets where there is a different approach in benchmarking. 1) Memory Read: Measures the bandwidth between the GPU device and the CPU, effectively measuring the performance the GPU could copy data from its own device memory into the system memory. It is also called Device-to-Host Bandwidth. [[[ The CPU benchmark measures the classic memory read bandwidth, the performance the CPU could read data from the system memory. ]]] 2) Memory Write: Measures the bandwidth between the CPU and the GPU device, effectively measuring the performance the GPU could copy data from the system memory into its own device memory. It is also called Host-to-Device Bandwidth. [[[ The CPU benchmark measures the classic memory write bandwidth, the performance the CPU could write data into the system memory. ]]] 3) Memory Copy: Measures the performance of the GPU's own device memory, effectively measuring the performance the GPU could copy data from its own device memory to another place in the same device memory. It is also called Device-to-Device Bandwidth. [[[ The CPU benchmark measures the classic memory copy bandwidth, the performance the CPU could move data in the system memory from one place to another. ]]] 4) Single-Precision FLOPS: Measures the classic MAD (Multiply-Addition) performance of the GPU, otherwise known as FLOPS (Floating-Point Operations Per Second), with single-precision (32-bit, "float") floating-point data. 5) Double-Precision FLOPS: Measures the classic MAD (Multiply-Addition) performance of the GPU, otherwise known as FLOPS (Floating-Point Operations Per Second), with double-precision (64-bit, "double") floating-point data. Not all GPUs support double-precision floating-point operations. For example, all current Intel desktop and mobile graphics devices only support single-precision floating-point operations. 6) 24-bit Integer IOPS: Measures the classic MAD (Multiply-Addition) performance of the GPU, otherwise known as IOPS (Integer Operations Per Second), with 24-bit integer ("int24") data. This special data type are defined in OpenCL on the basis that many GPUs are capable of executing int24 operations via their floating-point units, effectively increasing the integer performance by a factor of 3 to 5, as compared to using 32-bit integer operations. 7) 32-bit Integer IOPS: Measures the classic MAD (Multiply-Addition) performance of the GPU, otherwise known as IOPS (Integer Operations Per Second), with 32-bit integer ("int") data. 8) 64-bit Integer IOPS: Measures the classic MAD (Multiply-Addition) performance of the GPU, otherwise known as IOPS (Integer Operations Per Second), with 64-bit integer ("long") data. Most GPUs do not have dedicated execution resources for 64-bit integer operations, so instead they emulate the 64-bit integer operations via existing 32-bit integer execution units. In such case 64-bit integer performance could be very low. 9) Single-Precision Julia: Measures the single-precision (32-bit, "float") floating-point performance through the computation of several frames of the popular "Julia" fractal. 10) Double-Precision Mandel: Measures the double-precision (64-bit, "double") floating-point performance through the computation of several frames of the popular "Mandelbrot" fractal. Not all GPUs support double-precision floating-point operations. For example, all current Intel desktop and mobile graphics devices only support single-precision floating-point operations. ------------------------------------------------------------------------ As for the GPGPU Benchmark Panel's user interface: 1) You can use the checkboxes to enable or disable utilizing a specific GPU device or the CPU. The state of the CPU checkbox is remembered after closing and re-opening the panel. 2) You can launch the benchmarks for the selected devices by pushing the Start Benchmark button. In case you want to run all benchmarks, but only on the GPU(s), you can double-click on the GPU column label to do so. In case you only want to run the Memory Read benchmarks on both the GPU(s) and the CPU, you can double-click on the Memory Read label to do so. In case you only want to run the Memory Read benchmark on only the GPU(s), you can double-click on the cell where the requested result should appear after the benchmark is completed. 3) The benchmarks are executed simultaneously on all selected GPUs, using multiple threads and multiple OpenCL context, each with a single command queue. CPU benchmarks however are only launched after the GPU benchmarks are completed. It is currently not possible to run the GPU and CPU benchmarks simultaneously. 4) In case the system has multiple GPUs, the first results column will display an aggregated score for all GPUs. The individual GPU results are combined (added up), and the column label will read e.g. "4 GPUs". If you want to check the individual results, you can either uncheck some of the GPUs until just one GPU is left checked, or push the Results button to open the results window. 5) In case you've got exactly two GPU devices, and you disable the CPU test by unclicking its checkbox, the panel will switch to dual-GPU mode where the first column will be used for GPU1 results, and the second column will be used for GPU2 results. If after obtaining the results you want to check the combined performance of GPU1+GPU2, just check the CPU again, and the interface will switch back to the default layout. ------------------------------------------------------------------------ FAQ: Q: Is it possible to measure performance of OpenCL CPU devices? A: No, it's not available currently, because OpenCL CPU drivers are simply not suitable for proper benchmarking. They execute code a lot slower than native x86/x64 machine code or sometimes even regular multi-threaded C++ code. Q: Do AIDA64 GPGPU benchmarks use vectorized data types and unrolling techniques to boost performance? A: Yes, both, in order to make the job of OpenCL compilers a bit easier. On top of that, the OpenCL compiler may still use additional optimizations, like further unrolling, it is completely up to the OpenCL compiler. Q: Is the OpenCL-capable VIA chipset (VX11) supported? A: No, because currently there's no stable OpenCL compiler and OpenCL driver for VIA chipsets or processors. Q: Are OpenCL 2.0 and HSA supported on AMD Kaveri systems? A: Yes, except for the memory benchmarks. Memory benchmarks currently don't work with HSA, because the current AMD HSA implementation doesn't yet support forcing the usage of device memory, but instead it automatically assumes that allocated memory blocks are to be shared between the CPU and GPU. As soon as AMD's OpenCL 2.0 and HSA implementation gets more mature, these issues will be resolved. Q: Are the latest generation dGPUs, like AMD Radeon R9 290/290X, nVIDIA GeForce GTX Titan and GTX 780 fully supported? A: Yes, but on such dGPUs where clock boosting and/or throttling is used, it is very important to decide whether you want to measure the absolute maximum attainable performance, or the average performance. If you're looking for the absolute maximum scores, then make sure to start AIDA64 GPGPU Benchmarks when the video card is cool, and with power limits set to a relaxed value (AMD PowerControl). If you're looking for the average performance, then make sure to disable the CPU benchmarks, and execute the GPU benchmark methods at least 10 times right after each other, to properly heat the video card up. Q: Is OpenCL benchmarking under Windows 8.1 and Windows Server 2012 R2 supported? A: Yes, as long as the video drivers are properly installed. Q: On the Intel Core i7 "Haswell" processor, the CPU results are all considerably higher than the Intel HD Graphics 4600 "GT2" GPU results. How is that possible? A: AIDA64 CPU benchmarks are heavily optimized for Haswell and all other modern CPU architectures, and they utilize any available instruction set extensions like SSE, AVX, AVX2, FMA or XOP, and of course full vectorization as well. Using FMA and AVX2, a quad-core Haswell's x86/x64 part can indeed provide very high computing performance, well exceeding the performance of its GT2 iGPU. It is however much easier to write such optimized code for the iGPU via OpenCL, than for the CPU via machine code generator or x86/x64 assembly. ------------------------------------------------------------------------ You can try the new OpenCL GPGPU Benchmarks in the following new beta release of AIDA64 Extreme: http://www.aida64.com/downloads/aida64extremebuild2656b7hl0kzgtszip After upgrading to this new version, make sure to restart Windows to finalize the upgrade. Please let us know here in this topic if you've got any comments or ideas about the new benchmarks.

The External Applications feature is there to let you export the values from AIDA64 for processing by another application. That other application should be responsible of processing -- and if necessary, altering -- the labels and measured values. Regards, Fiery

Thank you. That looks fine, no issues in there. Do you have Asus AI Suite II installed? If yes, then it may cause a collision with AIDA64, so it may be best to uninstall AI Suite, or enable the option AIDA64 / main menu / File / Preferences / Stability / Asus ATKEX sensor support.

Please refer to the two PDF manuals published here: http://www.aida64.com/downloads/aida64business320zip In case you've got additional questions after going through those manuals, please let me know in this topic. But please note that this is an English language forum. Regards, Fiery

Please let me know (in English) what exactly is wrong with the motherboard temperature reading. If you believe the reading is inaccurate or invalid, then please compare the readings against Asus AI Suite or Asus PC Probe readings, and let us know what difference can you see.

Thank you for the feedback

Exactly The chipset page shows the capabilities of the chipset. It depends on the actual motherboard installation whether you've got DDR2 slots, DDR3 slots, or both.

Please upgrade to the latest beta version of AIDA64 Extreme available at: http://www.aida64.com/downloads/aida64extremebuild2638csfxl2d8mhzip After upgrading to this new version, make sure to restart Windows to finalize the upgrade. Let me know how it works

Please upgrade to the latest beta version of AIDA64 Extreme available at: http://www.aida64.com/downloads/aida64extremebuild2638csfxl2d8mhzip After upgrading to this new version, make sure to restart Windows to finalize the upgrade. Let me know how it works

Please upgrade to the latest beta version of AIDA64 Extreme available at: http://www.aida64.com/downloads/aida64extremebuild2638csfxl2d8mhzip After upgrading to this new version, make sure to restart Windows to finalize the upgrade. Let me know how it works

Thank you for the feedback

Yes it does.

Razer very quickly responded the following: "You can press and hold the Razer Home key until the Razer Task Manager appears. It should show all the running apps including yours (assumming you did not close it when you receive the de-activate). You can scroll until you find your app's last screen, then simply tap on it. When you're app gets published in Synapse and the user assigned it to a dynamic key, the user can simply go back to Razer Home and press that dynamic key. Your app would get re-activated." We'll work on getting AIDA64 published on Synapse

1) CPU Package Power: Make sure to upgrade to the latest beta version of AIDA64 Extreme available at: http://www.aida64.com/downloads/aida64extremebuild2631xjbvz0sn9czip After upgrading to this new version, make sure to restart Windows to finalize the upgrade. If the problem persists, then please right-click on the bottom status bar of AIDA64 main window --> CPU Debug --> CPUID & MSR Dump. Send us the file as an attachment or copy-paste the full dump into a forum post. 2) Vcore: After upgrading to the beta release I've linked above, make sure to verify Vcore against Gigabyte's EasyTune utility, at both idle and under full CPU load. If the values do not match, then please let me know both values (AIDA64 Vcore reading, EasyTune Vcore reading) at both states (idle, full load). 3) OCZ: After upgrading to the beta release I've linked above, please right-click on the bottom status bar of AIDA64 main window --> Disk Debug --> ATA Dump. Send us the file as an attachment or copy-paste the full dump into a forum post. Thanks, Fiery

Thank you for the feedback. I'm afraid the current Razer SDK doesn't implement a facility to handle such application switching. Or at least we cannot find any API calls to get back control over the LCD after you've switched to another application. We'll ask Razer about this, there must be a solution.