![]() Read more about CLBenchmark 1.1 Desktop Edition. High resolution video of CLBenchmark 1.1 Desktop Edition is available here. Minor stability and compatibility improvements.But you won't be able to deduce from that experiment that you'll get similar results on another program, or with different hardware. Improved network stability and security The problem with benchmarks is obviously that you only can objectively evaluate very specific things - say, the same program done in CUDA and OpenCL, on the same hardware (as you named a source).GPUs without display output like NVIDIA Tesla series now supported.NVIDIA Optimus devices now identified correctly.AMD Hybrid CrossfireX devices now identified correctly.The test results are listed in a transparent and public OpenCL performance database.ĬLBenchmark 1.1 Desktop Edition supports any standard-compliant OpenCL 1.1 implementation and it is compatible with every major vendor’s solution. ![]() ![]() Offering an unbiased way of testing and comparing the performance of implementations of OpenCL 1.1, CLBenchmark 1.1 Desktop Edition is an easy-to-use tool for comparing the computational performance of different platforms.ĬLBenchmark compares the strengths and weaknesses of different hardware architectures such as CPUs, GPUs and APUs. High-resolution video of CLBenchmark 1.1 Desktop Edition is available Like Blender, we also used the actual OctaneRender application to tests a heavier workload than what is included with the standard benchmark.Your browser does not support the video tag. OpenCL RAM benchmark measures combined read-then-write performance, also usable to benchmark OpenCL supporting compute cards/devices. This tool leverages the RT cores inside the GPUs when available and runs through a series of models to produce an overall, average score. How fast is your OpenCL Discover which OpenCL benchmarks and tools are available to help you evaluate your OpenCL performance and test your implementation. OTOY's OctaneBench is a standalone tool that gives users the ability to benchmark CPUs or NVIDIA GPUs using the company's OctaneRender engine. With this workload, the GeForce RTX 3090's additional compute resources and 24GB frame buffer come into play, and it ends up being roughly 3x - 4x faster than the GeForce RTX 3080 or Titan RTX. Moving over to a larger, much more complex model and performing a simultaneous viewport and final renders with Blender tells a totally different story. However, both cards are much faster than the Titan RTX. The Basemark CL benchmark package features workloads that are designed to stress an OpenCL implementation in a realistic way and provide performance measurement. That lead shrinks down to the less than 5% using OPTIX. Here, the GeForce RTX 3090 is about 16% faster than the RTX 3080 when using CUDA. CUDA obviously leverages the GeForce's CUDA cores, while OPTIX also incorporates the RT engines. In the two charts above, we have results from BlenderBench using the Classroom and BMW models, using either the CUDA or OPTIX code paths. Previously, using the CUDA code path with NVIDIA GPUs resulted in better performance, but OpenCL actually outperforms it in these tests now. CUDA and OpenCL code paths are available in these tests, but we used OpenCL on all cards to keep the playing field level. ![]() The Scientific Analysis benchmark runs though an array of General Matrix Multiply (GEMM), N-Body Simulations (NBDY), and Fast Fourier Transformation ops and reports the overall speed in FLOPs. SANDRA's GPGPU Image Processing benchmark runs through an array of filters on its reference data and offers up an aggregate score, derived from a multitude of individual results. Scientific Analysis And Image Processing OpenCL Tests 3DMark (Time Spy, Fire Strike, Port Royal) GPCBenchmark is an OpenCL based benchmark that evaluates the performance of OpenCL capable devices with a collection tests: global and local memory bandwidth, single and double precision floating point performance, common mathematics operations (256×256 matrix multiplcation ouch), image processing and encryption (SHA-1). ![]()
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