intel burn test results.

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Join Stack Overflow to learn, share knowledge, and build your career. On the system I'm using the maximum frequency under load is 2. It only has Intel burn test results gflops for bitcoin and the number of cores not Hardware threads is 4. I get about the same result with Eigen.

Is my calculation for the maximum wrong? What's the best efficiency for a Intel CPU for large dense matrix multiplication? Does anyone have a paper describing this? You can see on the plot they are all getting less that Here is my code for anyone that cares. I can get slight better results than this but not much better.

This is a situation where the structure of your algorithm can make a big difference in how it performs, but you will usually hit a wall at some point where you just can't get intel burn test results gflops for bitcoin faster because you're waiting on values to come from some higher level in the memory hierarchy. In addition, your theoretical numbers assume that you have sufficient instructions without data dependencies to keep all of the execution units tasked on every cycle.

This can be very difficult to do in practice. I'm not sure what the optimum throughput for a general matrix multiply would be, but check out this previous question for information on what you can do to maximize the instruction throughput. By posting your answer, you agree to the privacy policy and terms of service.

Email Sign Up or sign in with Google. It often requires writing assembly, unless you happen to hit on an intrinsic idiom that your compiler handles really well. I added some text on Eigen vs MKL.

Maybe my formula is off by a factor of 2? I found some code to profile MKL. They have a chart for the iK. That tells me my formula is correct and that my code and Eigen's is inefficient. Jason R 5, 2 26 I have heard of using multiple levels of blocking for L1, L2, L3.

I'm not doing that yet. I use loop unrolling to dealt with data dependencies. So if my code is inefficient then so is Eigen's. It doesn't seem to me that your code is significantly less efficient than one would expect to be able to get.

It sounds like you've done the right things to make sure your algorithm is as memory-friendly as possible. A properly-tiled matrix multiply intel burn test results gflops for bitcoin is never limited by memory bandwidth on modern architectures, including x The limiting constraint on performance is raw compute throughput.

Thanks, that's what I thought. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Intel burn test results gflops for bitcoin.

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