What else can millions of Ethereum 4GB graphics card mining machines do?

What else can millions of Ethereum 4GB graphics card mining machines do?

With the launch of the Ethereum 2.0 beacon chain, most users began to discuss whether mining machines can still perform Ethereum PoW mining?

Whether PoW mining machines can continue to mine is a matter of several years. The more immediate problem facing PoW miners is that the mining machines with 4GB graphics card memory in their hands can no longer mine.

Unlike Bitcoin mining, the mining algorithm used by Ethereum 1.0 is "Ethash", which is a memory-intensive algorithm. The DAG (directed acyclic graph) file generated by mining will be directly stored in the graphics card memory. This means that the graphics card memory needs to be larger than the size of the DAG file when mining.

On December 25, 2020, the Ethereum network DAG file reached 4GB at block height 11,520,000. For early Ethereum miners, the biggest problem they are facing is not the upcoming Ethereum 2.0 but the Ethereum DAG file that has exceeded 4GB.

ETH, ETC and other token DAG file sizes, image source: investoon

Previously, there were about 1.53 million to 3 million 4GB GPU miners in the market mining ETH, accounting for about 30% to 40% of the total computing power of the Ethereum network. BlockBeats has found that after the Ethereum DAG file exceeds 4GB, there are three ways for 4GB GPU miners to continue running.

Replace the operating system to extend the use time of the mining machine

Since the Windows operating system allocates up to about 600 MB of video memory to the virtual memory (VRAM), while Linux's virtual memory only occupies about 120 MB, the mining machine system can be switched from Windows to Linux to extend the Ethereum mining time, which is expected to be extended by 3 months.

Replace the mining machine video memory

Since the video memory is not enough, then increasing the video memory capacity by modifying the graphics card is also a solution. Currently, expanding to 8GB of video memory requires 8 256MB x 32bit GDDR5 video memory particles. Without calculating the labor cost, the modification cost of each graphics card is about 400 yuan. At present, many mining pools provide mining machine modification services.

Price of a 256MB x 32bit GDDR5 video memory chip

Change mining currency

Compared with the above two methods, a more convenient way is to mine with a different token. Currently, the tokens that can be used with 4GB graphics cards are mainly BEAM, ETC, RVN, and ZIL.

BEAM

BEAM is a cryptocurrency developed based on the Mimblewimble protocol. BEAM does not use DAG files, but uses the BeamHashIII hash algorithm.

ETC

On January 9, ETC announced that it was carrying out a network hard fork upgrade codenamed Thanos (ECIP-1099). The participating core developers and community members reached a consensus on October 2, 2020 to accept ECIP-1099. This upgrade effectively reduced the size of the DAG. This modified Ethash is also known as EtcHash. This will allow miners with 3GB and 4GB GPU systems to resume mining, etc., increase security and promote a more decentralized and healthy mining ecosystem.

RVN

RVN uses the Kawpow algorithm and is compatible with GPU mining, but it has high requirements for GPUs and consumes a lot of power.

ZIL

ZIL uses the same Ethash algorithm as Ethereum 1.0. Currently, its DAG size is 1.24GB and is expected to reach 4 GB in 2032. ZIL is very suitable for mining with 4GB graphics card miners, but its profit margin is not high.

BEAM, ETC, RVN, and ZIL can all be mined using 4GB memory mining machines, so which one is more suitable for miners? BlockBeats has compiled statistics on the liquidity and returns of these projects:

Of the four tokens mentioned above, only ETC, RVN, and BEAM can currently be mined using AMD RX 580 4GB, and there is net profit. Among them, the highest profit is BEAM, which has the lowest market capitalization ranking and daily trading volume, followed by RVN.

In summary, RVN may be the best token that can be mined with a 4GB video memory mining machine under the current circumstances.

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