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Which typically would include either the exact RPC call parameters, or example of code where you invoke go-ethereum as a library. I don't even know what that thing you pasted is -- I'm guessing it's debug output from some random points in the codebase? A declarative, efficient, and flexible JavaScript library for building user interfaces. JavaScript JS is a lightweight interpreted programming language with first-class functions. A server is a program made to process requests and deliver data to clients.

Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently. We are working to build community through open source technology. NB: members must have two-factor auth. GithubHelp home page GithubHelp Search. Thanks for the suggestion! I've updated the draft above. TransactionByHash context.

Collectives on Stack Overflow. Learn more. Ask Question. Asked 4 years, 4 months ago. Modified 3 years, 8 months ago. Viewed times. Presumably contracts don't jump to invalid destinations on purpose? If anyone could explain how jumps and jump destinations are resolved I would be very grateful. Improve this question.

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But this actually isn't AMD's best overall showing. At the same time, power requirements dropped substantially, from W to W. However, the memory proves the deciding factor once again. That resulted in a MHz clock compared to MHz at stock, but fan speed was higher this time.

Boosting the clocks back to 2. The efficiency looks good, but the raw hashrate is definitely lacking — it's only marginally faster than a RX 8GB from five years back. After the testing we've completed, one thing we wanted to do was look at real-world profitability from mining. There's a reason people do this, and results can vary quite a bit depending on your specific hardware.

We've used the optimal tuned settings, as well as power draw figures. However, note that the power draw we're reporting doesn't include PSU inefficiencies or power for the rest of the PC. We're mostly looking at reference models as well, which often aren't the best option, but here's how our data compares to what NiceHash reports.

There are some interesting results. Our stance is that this is a Very Bad Idea tm. Not only will the fans make a lot of noise, but they're also destined to fail sooner rather than later. If you're okay replacing the card's fans in the future, or if you want to mod the card with better cooling pads in the first place, you can definitely achieve the NiceHash performance figures.

Power use as measured using Powenetics would of course increase. We were relatively close on the Ti performance, and our earlier power data showed much better results than NiceHash, but now those figures have been updated and are slightly lower than our measured power. The RTX meanwhile ended up with similar performance, but our power results were significantly higher — perhaps our EVGA sample just wasn't a good starting point.

The current thinking for a lot of miners is that Nvidia's RTX series cards are superior to AMD, but that's really only true if you look at pure hashrates on the and Factor in power efficiency and things are much closer. Besides, it's not like you can buy any of these GPUs right now — unless you're willing to fork out a lot of money or have some good industry contacts for building your mining farm.

The principles we've outlined above generally apply to the older GPUs as well. We're going to skip all the baseline performance metrics this time, and just jump straight to optimized performance. Note that outside of the RX and , and the three GTX variants, all of our tests were done using the reference models from AMD and Nvidia, which tend to be more of a baseline or worst-case scenario for most GPUs.

We'll list our optimized settings below, but here are the results. Our Vega cards are also reference models and were far more finnicky than other GPUs. For Nvidia's Turing GPUs, performance again correlates pretty much directly with memory bandwidth, though with a few interesting exceptions. Notice that the Super, Super, and Super all end up with nearly identical performance?

That's not an error. The odd bit is that the Super requires substantially higher memory clocks to get there. Most likely the memory timings on the GDDR6 in the Super are more relaxed looser , so even though bandwidth is higher, bandwidth plus latency ends up balancing out. The Ti and Super are basically the same speed, though we had better luck with memory overclocking on the Super. That reduces power use and temperatures and boosts overall efficiency.

Stepping back one generation further to Pascal GTX series , the approach changes a bit. Maximum memory clocks are still critical, but core clocks start to matter more—the architecture isn't tuned for compute as much as Turing and Ampere. We got our best results by overclocking the GPU core and memory speed, but then setting a power limit. Tweaking AMD's previous generation GPUs is a bit different, in that rather than limiting the power, the best approach is to tune the voltage and clock speed.

Not surprisingly, the older the GPUs get, the lower the hash rates and efficiency become. Let's start with the previous generation and move back from there. Move back to the Vega architecture and the large memory bandwidth that comes from HBM2 comes into play. But Vega was also a power-hungry architecture, and it benefits from turning down the GPU clocks.

That gave mining clocks of MHz. Vega 64 and Vega 56 used similar settings, but half the memory capacity and bus width limits performance quite a bit relative to the Radeon VII. Also, our results on the reference blower cards are probably far less than ideal—just about any custom Vega card would be a better choice than these blowers. We experienced a lot of crashing on the two Vega cards while trying to tune performance.

And then there's Polaris. Much like the Pascal GPUs, our tuning efforts took more time and effort. Besides setting a low voltage of mV, depending on the card, we set the memory timings to level2 in Radeon Settings, and that gave the best results with reasonable power use. Here's a gallery of all the 'tuned' settings we used for the legacy cards. Use at your own risk, and know that some cards prefer different miner software or simply fail to work with certain miners.

Is it possible to improve over our results? This is just a baseline set of performance figures and data, using our specific samples. Again, non-reference cards often perform a bit better, and if you want to research VBIOS flashing and hardware modding it's possible to hit higher hash rates.

But out of the box, these are numbers that just about any card using one of these GPUs should be able to match. This brings us to the final point we want to make. Suppose you already have a graphics card and want to mine using your GPU's spare cycles. In that case, it might be worth considering, particularly if you live in an area where power isn't super expensive.

At the same time, we strongly recommend against 'redlining' your card for maximum hashrate at all costs. They will burn out if you run them that way. We also have serious concerns with any component temperature that's consistently at or above C or really, even 90C. Will it be long enough to recover the cost of the card? That's the big unknown. Here's the thing to remember: Cryptocurrencies are extremely volatile.

This means that, as fast as the price shot up, it could plummet just as quickly. At one point, it might have been possible to break even on the cost of a new GPU in a few months. These days, it would take more than a year at current rates, assuming nothing changes. It could go up, but the opposite is more likely.

Just ask the GameStop 'investors' how that worked out if you think the sky's the limit. Again, if you already have a GPU, putting it into service isn't a terrible idea — it's your hardware, do with it what you please. Paying extreme prices for mid-range hardware to try and build your own personal mining mecca, on the other hand, is a big risk.

You might do fine, you might do great, or you might end up with a lot of extra PC hardware and debt. Plus, what about all the gamers that would love to buy a new GPU right now and they can't? Somebody, please think of the gamers!

Anyway, if you're looking for additional information, here is our list of the best mining GPUs , and we've checked profitability and daily returns of each GPU. Just remember to account for power costs and cash out enough coins to cover that, and then hopefully you won't get caught holding the bag.

From the first S3 Virge '3D decelerators' to today's GPUs, Jarred keeps up with all the latest graphics trends and is the one to ask about game performance. Tom's Hardware Tom's Hardware. Image 1 of Image 2 of Image 3 of Image 4 of Image 5 of Image 6 of Image 7 of Image 8 of Image 9 of Image 10 of Image 11 of The program counter depends on the opcode.

How much many bytes does a opcode push into the stack,etc. Stack Overflow for Teams — Start collaborating and sharing organizational knowledge. Create a free Team Why Teams? Collectives on Stack Overflow. Learn more. Ask Question. Asked 4 years, 4 months ago. Modified 3 years, 8 months ago.

Viewed times. Presumably contracts don't jump to invalid destinations on purpose? If anyone could explain how jumps and jump destinations are resolved I would be very grateful. Improve this question. Rob N Rob N 31 2 2 bronze badges. Add a comment. Sorted by: Reset to default. Highest score default Date modified newest first Date created oldest first. Help us improve our answers. Are the answers below sorted in a way that puts the best answer at or near the top?

Improve this answer. If the condition is False, it will just increase the program counter by 1. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password.