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Gpu hash calculator
Gpu hash calculator












#GPU HASH CALCULATOR PC#

Video Card Overclockīasic version of the OuterVision Power Supply Calculator allows users to quickly estimate power consumption with minimal selection of PC parts. Building cryptocurrency mining rig? Check our Mining Rig Builder tool. Are you building a modern gaming PC, low power HTPC media server, or maybe you need to figure out power requirements for a rack in a data center? We've got you covered - OuterVision PSU Calculator will help you to select a suitable power supply unit and even Uninterruptible Power Supply (UPS) for your system. OuterVision Power Supply Calculator is the most accurate PC power consumption calculator available and is trusted by computer enthusiasts, PC hardware and power supply manufacturers across the Globe. If that were true, I’d advise you not to stop at 13.OuterVision ® Power Supply Calculator Real Power Consumption It’s amazing how prevalent this line of thinking is when it comes to streams. If i use 13 streams will the hashing power be 13x faster ? If you want to learn what streams are for, google “gtc cuda streams” and take the first hit. Piecemeal Q+A “Socratic” method might seem “efficient” but is actually quite inefficient for learning a body of knowledge like this, IMO. I know you’d like to learn it in 5 minutes, but in my experience it takes longer than that. Please avail yourself of an organized introduction to CUDA. A kernel with enough blocks will fill all the SMs on a GPU, and this is generally desirable. If I run a single kernel, there is only one SM working ? If you don’t believe me, print out those quantities. Sha256_kernel > (g_out, g_hash_out, g_found, d_in, input_size, difficulty, nonce) #define NUMBLOCKS (SHA_PER_ITERATIONS + BLOCK_SIZE - 1) / BLOCK_SIZE I looked at this: #define BLOCK_SIZE 1024 I don’t understand why you are talking about 4 blocks because I run 10 blocks of 1024 threads. Here’s the cpu version : GitHub - moffa13/SHA256Speed Here’s the github : GitHub - moffa13/SHA256CUDA Please tell me what should be changed in order to optimize this :) Is it the right way, calling multiple times the kernel ? If not, I rerun the kernel with an updated nonce offset. After the kernel call, I run cudaDeviceSynchronize and I check if the global variable is set to 1. If one thread finds the right nonce, a global variable is set to 1 then the other threads return. One thread does one hash as it can’t be parallelised. What I’m doing is that I run a for loop which starts a kernel and processes hashes. I’m pretty sure I can optimize this but I don’t know how. I created the same program but for cpu and I can do over 6 millions hashes in a second. You enter a string then it finds an associated nonce prepended to the input string matching a sha256 with some number of zeros at the beggining.įor example if I want a difficulty of 6 and I put “moffa13” as input string, the program returnsĦ253010moffa13 which has this associated hash :Ġ000002dece0c0f5791305f53bfd5116966ea97a9604984cbb50891f243e5641 (6 zeros before) I’m new to cuda development, I tried to do a program which illustrates the bitcoin mining difficulty.












Gpu hash calculator