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Zen and Vega DDR4 Memory Scaling on AMD's APUs


PT KONTAK PERKASA FUTURES - We have previously explored the importance of memory scaling within AMDs Ryzen CPUs: the question being answered today is how much of an effect on performance does the memory frequency have when Zen is paired with AMD’s own Vega graphics core. We run a complete suite of tests on AMD's Ryzen 3 2200G ($99) and Ryzen 5 2400G ($169) APUs with memory speeds from DDR4-2133 to DDR4-3466 using a kit of G.Skill Ripjaws V.

Memory Scaling on AMD Ryzen APUs

PT KONTAK PERKASA FUTURES - While adding Vega to Zen may be a new concept, the premise of the APU combing compute and graphics on the same chip remains the same. Graphics is often a memory bound operation - the speed at which the data can be accessed by the graphics is directly tied to the frame rate, and we have seen on chips in the past that the speed of the memory (or an interim cache) can vastly help accelerate the performance of the graphics. Graphics is usually the focus here, as faster memory only assists CPU workloads that are memory limited.

PT KONTAK PERKASA FUTURES - One of the main issues with memory right now is pricing. With the price of DDR4 having risen over the course of 2017 and with no signs of slowing in 2018, building a new desktop system has looked more expensive over the course of the last couple of years: the inflation of GPU pricing has also certainly contributed to those woes. While the general outlook on the current DDR4 DRAM market is that for a user wanting extra speed, more money must be spent is true, how that equates into actual performance becomes more relevant than ever before.

The price of this memory when launched was $142, which decreased down to as low as $57 on sale but was an average of $75 during early 2016. Over the course of 2017 and 2018, this very popular memory kit is now trading at $179, having reached a high of $200. To put that in perspective, this kit launched at a cost of $8.88 per GB, went down as low as $3.56 per GB, and is now at $11.19 per GB. This is almost certainly a sellers market, not a buyers market. People are often spending money on capacity over speed. The goal of this article is to determine how much speed actually matters, especially when we look at lower-cost processors like the AMD Ryzen APUs.

The Infinity Fabric (hereafter shortened to IF) consists of two fabric planes: the Scalable Control Fabric (SCF) and the Scalable Data Fabric (SDF). The SCF is all about control: power management, remote management and security and IO. Essentially when data has to flow to different elements of the processor other than main memory, the SCF is in control. The SDF is where main memory access comes into play. There's still management here - being able to organize buffers and queues in order of priority assists with latency, and the organization also relies on a speedy implementation. The slide below is aimed more towards the IF implementation in AMD's server products, such as power control on individual memory channels, but still relevant to accelerating consumer workflow.

AMD's goal with IF was to develop an interconnect that could scale beyond CPUs, groups of CPUs, and GPUs. In the EPYC server product line, IF connects not only cores within the same piece of silicon, but silicon within the same processor and also processor to processor. Two important factors come into the design here: power (usually measured in energy per bit transferred) and bandwidth.

Source : anandtech.com

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