The performance improvement with the new Zen4 TrPRO over the Zen3 TrPRO is very impressive!
My first recommendation for a Scientific and Engineering workstation CPU would now be the AMD Zen4 architecture as either Zen4 Threadripper PRO or Zen4 EPYC for multi-socket systems.
Evaluating the speed of GeForce RTX 40-Series GPUs using NVIDIA’s TensorRT-LLM tool for benchmarking GPU inference performance.
Results and thoughts with regard to testing a variety of Stable Diffusion training methods using multiple GPUs.
I was prompted to do some testing by a commenter on one of my recent posts. They had concerns about problems with dual NVIDIA RTX4090s on AMD Threadripper Pro platforms. I ran some applications to reproduce the problems reported above and tried to dig deeper into the issues with more extensive testing. The included table below tells all!
This post is a first-look at performance of the Ryzen7 7950x CPU using the latest AMD compiler release with support for Zen4 arch including AVX512 vector instructions. Performance is tested using the HPC standard benchmarks, HPL (High Performance Linpack), HPCG (High Performance Conjugate Gradient) and the newer HPC Top500 benchmark, HPL-MxP (formerly HPL-AI).
We have a new collection of GPU accelerated Molecular Dynamics benchmark packages put together for GROMACS, NAMD 2, and NAMD 3-alpha10. (The benchmark packages will be available to the public soon.) In this post we present results for,
– 3 applications: GROMACS, NAND 2 and NAMD 3alpha10,
– 8 MD simulations,
– 12 different NVIDIA GPUs,
– 96 total results.
The single socket version of Intel third generation Xeon SP is out, the Ice Lake Xeon W 33xx. This is a much better platform with faster large capacity 8 channel memory and PCIe v4 with plenty of lanes. The new Intel platform is very much like the AMD Threadripper Pro (single socket version of EPYC Rome) so this is the obvious comparison to make. Read on to see how the numerical computing testing went!
For computing tasks like Machine Learning and some Scientific computing the RTX3080TI is an alternative to the RTX3090 when the 12GB of GDDR6X is sufficient. (Compared to the 24GB available of the RTX3090). 12GB is in line with former NVIDIA GPUs that were “work horses” for ML/AI like the wonderful 2080Ti.
The NVIDIA A100 (Compute) GPU is an extraordinary computing device. It’s not just for ML/AI types of workloads. General scientific computing tasks requiring high performance numerical linear algebra run exceptionally well on the A100.
The new Intel Rocket Lake CPUs have been officially released. There were numerous posts and reviews before the official release date of March 30 2021, but I haven’t seen anything about the numerical compute performance. I’ve had access to a Core-i9 11900KF 8-core CPU and have compared it with (my own) AMD 5800X system.
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