--- title: Ethash description: "Ethash algoritmasına detaylı bir bakış." lang: tr --- Ethash, Ethereum'un İş Kanıtı (PoW) madencilik algoritmasıydı. İş Kanıtı (PoW) artık **tamamen kapatıldı** ve Ethereum artık bunun yerine [Hisse Kanıtı (PoS)](/developers/docs/consensus-mechanisms/pos/) kullanılarak güvence altına alınıyor. [Birleşme](/roadmap/merge/), [Hisse Kanıtı (PoS)](/developers/docs/consensus-mechanisms/pos/) ve [staking](/staking/) hakkında daha fazla bilgi edinin. Bu sayfa tarihi ilgi amaçlıdır! Ethash, [Dagger-Hashimoto](/developers/docs/consensus-mechanisms/pow/mining/mining-algorithms/dagger-hashimoto) algoritmasının değiştirilmiş bir versiyonudur. Ethash İş Kanıtı (PoW) [bellek zorludur (memory hard)](https://wikipedia.org/wiki/Memory-hard_function), bu da algoritmayı ASIC'e dirençli hale getirdiği düşünülen bir özellikti. Ethash ASIC'leri sonunda geliştirildi ancak GPU madenciliği, İş Kanıtı (PoW) kapatılana kadar hala geçerli bir seçenekti. Ethash, Ethereum dışındaki diğer İş Kanıtı (PoW) ağlarında diğer coin'lerin madenciliğini yapmak için hala kullanılmaktadır. ## Ethash nasıl çalışır? {#how-does-ethash-work} Bellek zorluğu, nonce ve blok başlığına bağlı sabit bir kaynağın alt kümelerinin seçilmesini gerektiren bir İş Kanıtı (PoW) algoritması ile elde edilir. Bu kaynağa (birkaç gigabayt boyutunda) DAG denir. DAG her 30000 blokta bir değiştirilir, bu ~125 saatlik pencereye bir dönem (yaklaşık 5,2 gün) denir ve oluşturulması biraz zaman alır. DAG yalnızca blok yüksekliğine bağlı olduğundan önceden oluşturulabilir, ancak oluşturulmamışsa istemcinin bir blok üretmek için bu sürecin sonuna kadar beklemesi gerekir. İstemciler DAG'leri önceden oluşturup önbelleğe almazlarsa, ağ her dönem geçişinde büyük bir blok gecikmesi yaşayabilir. İş Kanıtı'nı (PoW) doğrulamak için DAG'nin oluşturulmasına gerek olmadığını, bunun da esasen hem düşük CPU hem de küçük bellek ile doğrulamaya izin verdiğini unutmayın. Algoritmanın izlediği genel yol aşağıdaki gibidir: 1. O noktaya kadar olan blok başlıkları taranarak her blok için hesaplanabilen bir **tohum (seed)** vardır. 2. Tohumdan, **16 MB'lık sözde rastgele bir önbellek** hesaplanabilir. Hafif istemciler önbelleği depolar. 3. Önbellekten, veri kümesindeki her bir öğenin önbellekteki yalnızca az sayıda öğeye bağlı olması özelliğiyle **1 GB'lık bir veri kümesi** oluşturabiliriz. Tam istemciler ve madenciler veri kümesini depolar. Veri kümesi zamanla doğrusal olarak büyür. 4. Madencilik, veri kümesinden rastgele dilimler almayı ve bunları birlikte hashlemeyi içerir. Doğrulama, ihtiyacınız olan veri kümesinin belirli parçalarını yeniden oluşturmak için önbelleği kullanarak düşük bellekle yapılabilir, bu nedenle yalnızca önbelleği depolamanız gerekir. Büyük veri kümesi her 30000 blokta bir güncellenir, bu nedenle bir madencinin çabasının büyük çoğunluğu veri kümesinde değişiklik yapmak değil, onu okumak olacaktır. ## Tanımlar {#definitions} Aşağıdaki tanımları kullanıyoruz: ``` WORD_BYTES = 4 # kelimedeki baytlar DATASET_BYTES_INIT = 2**30 # başlangıçtaki veri kümesindeki baytlar DATASET_BYTES_GROWTH = 2**23 # dönem başına veri kümesi büyümesi CACHE_BYTES_INIT = 2**24 # başlangıçtaki önbellekteki baytlar CACHE_BYTES_GROWTH = 2**17 # dönem başına önbellek büyümesi CACHE_MULTIPLIER=1024 # Önbelleğe göre DAG'nin boyutu EPOCH_LENGTH = 30000 # dönem başına bloklar MIX_BYTES = 128 # karışımın genişliği HASH_BYTES = 64 # bayt cinsinden hash uzunluğu DATASET_PARENTS = 256 # her veri kümesi öğesinin ebeveyn sayısı CACHE_ROUNDS = 3 # önbellek üretimindeki tur sayısı ACCESSES = 64 # hashimoto döngüsündeki erişim sayısı ``` ### 'SHA3' kullanımı {#sha3} Ethereum'un gelişimi SHA3 standardının gelişimiyle aynı zamana denk geldi ve standartlar süreci, kesinleşmiş hash algoritmasının dolgusunda (padding) geç bir değişiklik yaptı, bu nedenle Ethereum'un "sha3_256" ve "sha3_512" hash'leri standart sha3 hash'leri değil, diğer bağlamlarda genellikle "Keccak-256" ve "Keccak-512" olarak adlandırılan bir varyanttır. Tartışmalara bakın, örn. [burada](https://eips.ethereum.org/EIPS/eip-1803), [burada](https://ethereum.stackexchange.com/questions/550/which-cryptographic-hash-function-does-ethereum-use) veya [burada](https://bitcoin.stackexchange.com/questions/42055/what-is-the-approach-to-calculate-an-ethereum-address-from-a-256-bit-private-key/42057#42057). Aşağıdaki algoritmanın açıklamasında "sha3" hash'lerine atıfta bulunulduğundan lütfen bunu aklınızda bulundurun. ## Parametreler {#parameters} Ethash'in önbelleği ve veri kümesi için parametreler blok numarasına bağlıdır. Önbellek boyutu ve veri kümesi boyutu doğrusal olarak büyür; ancak, döngüsel davranışa yol açan tesadüfi düzenlilik riskini azaltmak için her zaman doğrusal olarak büyüyen eşiğin altındaki en yüksek asal sayıyı alırız. ```python def get_cache_size(block_number): sz = CACHE_BYTES_INIT + CACHE_BYTES_GROWTH * (block_number // EPOCH_LENGTH) sz -= HASH_BYTES while not isprime(sz / HASH_BYTES): sz -= 2 * HASH_BYTES return sz def get_full_size(block_number): sz = DATASET_BYTES_INIT + DATASET_BYTES_GROWTH * (block_number // EPOCH_LENGTH) sz -= MIX_BYTES while not isprime(sz / MIX_BYTES): sz -= 2 * MIX_BYTES return sz ``` Veri kümesi ve önbellek boyutu değerlerinin tabloları ekte verilmiştir. ## Önbellek oluşturma {#cache-generation} Şimdi, bir önbellek üretmek için işlevi belirtiyoruz: ```python def mkcache(cache_size, seed): n = cache_size // HASH_BYTES # Başlangıç veri kümesini sırayla üret o = [sha3_512(seed)] for i in range(1, n): o.append(sha3_512(o[-1])) # Randmemohash'in düşük turlu bir sürümünü kullan for _ in range(CACHE_ROUNDS): for i in range(n): v = o[i][0] % n o[i] = sha3_512(map(xor, o[(i-1+n) % n], o[v])) return o ``` Önbellek üretim süreci, önce 32 MB belleğin sırayla doldurulmasını, ardından Sergio Demian Lerner'ın [_Strict Memory Hard Hashing Functions_ (2014)](http://www.hashcash.org/papers/memohash.pdf) adlı eserindeki _RandMemoHash_ algoritmasının iki geçişinin gerçekleştirilmesini içerir. Çıktı, 524288 adet 64 baytlık değerden oluşan bir kümedir. ## Veri toplama işlevi {#date-aggregation-function} Bazı durumlarda XOR'un birleşmeli olmayan (non-associative) bir alternatifi olarak [FNV hash](https://en.wikipedia.org/wiki/Fowler%E2%80%93Noll%E2%80%93Vo_hash_function)'ten esinlenen bir algoritma kullanıyoruz. Asal sayıyı sırayla bir bayt (sekizli) ile çarpan FNV-1 spesifikasyonunun aksine, asal sayıyı tam 32 bitlik girdiyle çarptığımıza dikkat edin. ```python FNV_PRIME = 0x01000193 def fnv(v1, v2): return ((v1 * FNV_PRIME) ^ v2) % 2**32 ``` Lütfen unutmayın, Sarı Bülten bile fnv'yi v1\*(FNV_PRIME ^ v2) olarak belirtse de, mevcut tüm uygulamalar tutarlı bir şekilde yukarıdaki tanımı kullanır. ## Tam veri kümesi hesaplaması {#full-dataset-calculation} Tam 1 GB'lık veri kümesindeki her 64 baytlık öğe aşağıdaki gibi hesaplanır: ```python def calc_dataset_item(cache, i): n = len(cache) r = HASH_BYTES // WORD_BYTES # karışımı başlat mix = copy.copy(cache[i % n]) mix[0] ^= i mix = sha3_512(mix) # i'ye dayalı çok sayıda rastgele önbellek düğümü ile fnv işleminden geçir for j in range(DATASET_PARENTS): cache_index = fnv(i ^ j, mix[j % r]) mix = map(fnv, mix, cache[cache_index % n]) return sha3_512(mix) ``` Esasen, sözde rastgele seçilmiş 256 önbellek düğümünden gelen verileri birleştiriyoruz ve veri kümesi düğümünü hesaplamak için bunu hashliyoruz. Tüm veri kümesi daha sonra şu şekilde oluşturulur: ```python def calc_dataset(full_size, cache): return [calc_dataset_item(cache, i) for i in range(full_size // HASH_BYTES)] ``` ## Ana döngü {#main-loop} Şimdi, belirli bir başlık ve nonce için nihai değerimizi üretmek amacıyla tam veri kümesinden verileri topladığımız ana "hashimoto" benzeri döngüyü belirtiyoruz. Aşağıdaki kodda, `header`, _kesilmiş_ bir blok başlığının, yani **mixHash** ve **nonce** alanları hariç tutulmuş bir başlığın RLP temsilinin SHA3-256 _hash_'ini temsil eder. `nonce`, büyük uçlu (big-endian) sırasındaki 64 bitlik işaretsiz bir tamsayının sekiz baytıdır. Yani `nonce[::-1]`, bu değerin sekiz baytlık küçük uçlu (little-endian) temsilidir: ```python def hashimoto(header, nonce, full_size, dataset_lookup): n = full_size / HASH_BYTES w = MIX_BYTES // WORD_BYTES mixhashes = MIX_BYTES / HASH_BYTES # başlık+nonce'u 64 baytlık bir tohuma birleştir s = sha3_512(header + nonce[::-1]) # karışımı çoğaltılmış s ile başlat mix = [] for _ in range(MIX_BYTES / HASH_BYTES): mix.extend(s) # rastgele veri kümesi düğümlerini karışıma ekle for i in range(ACCESSES): p = fnv(i ^ s[0], mix[i % w]) % (n // mixhashes) * mixhashes newdata = [] for j in range(MIX_BYTES / HASH_BYTES): newdata.extend(dataset_lookup(p + j)) mix = map(fnv, mix, newdata) # karışımı sıkıştır cmix = [] for i in range(0, len(mix), 4): cmix.append(fnv(fnv(fnv(mix[i], mix[i+1]), mix[i+2]), mix[i+3])) return { "mix digest": serialize_hash(cmix), "result": serialize_hash(sha3_256(s+cmix)) } def hashimoto_light(full_size, cache, header, nonce): return hashimoto(header, nonce, full_size, lambda x: calc_dataset_item(cache, x)) def hashimoto_full(full_size, dataset, header, nonce): return hashimoto(header, nonce, full_size, lambda x: dataset[x]) ``` Esasen, 128 bayt genişliğinde bir "karışım" (mix) tutuyoruz ve tam veri kümesinden art arda sırayla 128 bayt alıp bunu karışımla birleştirmek için `fnv` işlevini kullanıyoruz. Algoritmanın her turunun her zaman RAM'den tam bir sayfa getirmesi ve böylece ASIC'lerin teorik olarak kaçınabileceği çeviri arabelleği (TLB) isabet kayıplarını en aza indirmesi için 128 baytlık sıralı erişim kullanılır. Bu algoritmanın çıktısı istenen hedefin altındaysa, nonce geçerlidir. Sonundaki ekstra `sha3_256` uygulamasının, en azından küçük bir miktar iş yapıldığını kanıtlamak için sağlanabilecek bir ara nonce olmasını sağladığına dikkat edin; bu hızlı dış İş Kanıtı (PoW) doğrulaması, anti-DDoS amaçları için kullanılabilir. Ayrıca sonucun tarafsız, 256 bitlik bir sayı olduğuna dair istatistiksel güvence sağlamaya da hizmet eder. ## Madencilik {#mining} Madencilik algoritması aşağıdaki gibi tanımlanır: ```python def mine(full_size, dataset, header, difficulty): # aynı basamaktaki hash ile karşılaştırmak için hedefi sıfırla doldur target = zpad(encode_int(2**256 // difficulty), 64)[::-1] from random import randint nonce = randint(0, 2**64) while hashimoto_full(full_size, dataset, header, nonce) > target: nonce = (nonce + 1) % 2**64 return nonce ``` ## Tohum hash'ini tanımlama {#seed-hash} Belirli bir bloğun üzerinde madencilik yapmak için kullanılacak tohum hash'ini hesaplamak amacıyla aşağıdaki algoritmayı kullanıyoruz: ```python def get_seedhash(block): s = '\x00' * 32 for i in range(block.number // EPOCH_LENGTH): s = serialize_hash(sha3_256(s)) return s ``` Sorunsuz madencilik ve doğrulama için, gelecekteki tohum hash'lerini ve veri kümelerini ayrı bir iş parçacığında (thread) önceden hesaplamanızı önerdiğimizi unutmayın. ## Daha fazla okuma {#further-reading} _Size yardımcı olan bir topluluk kaynağı mı biliyorsunuz? Bu sayfayı düzenleyin ve ekleyin!_ ## Ek {#appendix} Yukarıdaki Python spesifikasyonunu kod olarak çalıştırmakla ilgileniyorsanız, aşağıdaki kod başa eklenmelidir. ```python import sha3, copy # Küçük uçlu bit sıralamasını varsayar (Intel mimarileriyle aynı) def decode_int(s): return int(s[::-1].encode('hex'), 16) if s else 0 def encode_int(s): a = "%x" % s return '' if s == 0 else ('0' * (len(a) % 2) + a).decode('hex')[::-1] def zpad(s, length): return s + '\x00' * max(0, length - len(s)) def serialize_hash(h): return ''.join([zpad(encode_int(x), 4) for x in h]) def deserialize_hash(h): return [decode_int(h[i:i+WORD_BYTES]) for i in range(0, len(h), WORD_BYTES)] def hash_words(h, sz, x): if isinstance(x, list): x = serialize_hash(x) y = h(x) return deserialize_hash(y) def serialize_cache(ds): return ''.join([serialize_hash(h) for h in ds]) serialize_dataset = serialize_cache # sha3 hash işlevi, 64 bayt çıktı verir def sha3_512(x): return hash_words(lambda v: sha3.sha3_512(v).digest(), 64, x) def sha3_256(x): return hash_words(lambda v: sha3.sha3_256(v).digest(), 32, x) def xor(a, b): return a ^ b def isprime(x): for i in range(2, int(x**0.5)): if x % i == 0: return False return True ``` ### Veri Boyutları {#data-sizes} Aşağıdaki arama tabloları, veri boyutları ve önbellek boyutlarının yaklaşık 2048 tablo haline getirilmiş dönemini sağlar. ```python def get_datasize(block_number): return data_sizes[block_number // EPOCH_LENGTH] def get_cachesize(block_number): return cache_sizes[block_number // EPOCH_LENGTH] data_sizes = [ 1073739904, 1082130304, 1090514816, 1098906752, 1107293056, 1115684224, 1124070016, 1132461952, 1140849536, 1149232768, 1157627776, 1166013824, 1174404736, 1182786944, 1191180416, 1199568512, 1207958912, 1216345216, 1224732032, 1233124736, 1241513344, 1249902464, 1258290304, 1266673792, 1275067264, 1283453312, 1291844992, 1300234112, 1308619904, 1317010048, 1325397376, 1333787776, 1342176128, 1350561664, 1358954368, 1367339392, 1375731584, 1384118144, 1392507008, 1400897408, 1409284736, 1417673344, 1426062464, 1434451072, 1442839168, 1451229056, 1459615616, 1468006016, 1476394112, 1484782976, 1493171584, 1501559168, 1509948032, 1518337664, 1526726528, 1535114624, 1543503488, 1551892096, 1560278656, 1568669056, 1577056384, 1585446272, 1593831296, 1602219392, 1610610304, 1619000192, 1627386752, 1635773824, 1644164224, 1652555648, 1660943488, 1669332608, 1677721216, 1686109312, 1694497664, 1702886272, 1711274624, 1719661184, 1728047744, 1736434816, 1744829056, 1753218944, 1761606272, 1769995904, 1778382464, 1786772864, 1795157888, 1803550592, 1811937664, 1820327552, 1828711552, 1837102976, 1845488768, 1853879936, 1862269312, 1870656896, 1879048064, 1887431552, 1895825024, 1904212096, 1912601216, 1920988544, 1929379456, 1937765504, 1946156672, 1954543232, 1962932096, 1971321728, 1979707264, 1988093056, 1996487552, 2004874624, 2013262208, 2021653888, 2030039936, 2038430848, 2046819968, 2055208576, 2063596672, 2071981952, 2080373632, 2088762752, 2097149056, 2105539712, 2113928576, 2122315136, 2130700672, 2139092608, 2147483264, 2155872128, 2164257664, 2172642176, 2181035392, 2189426048, 2197814912, 2206203008, 2214587264, 2222979712, 2231367808, 2239758208, 2248145024, 2256527744, 2264922752, 2273312128, 2281701248, 2290086272, 2298476672, 2306867072, 2315251072, 2323639168, 2332032128, 2340420224, 2348808064, 2357196416, 2365580416, 2373966976, 2382363008, 2390748544, 2399139968, 2407530368, 2415918976, 2424307328, 2432695424, 2441084288, 2449472384, 2457861248, 2466247808, 2474637184, 2483026816, 2491414144, 2499803776, 2508191872, 2516582272, 2524970368, 2533359232, 2541743488, 2550134144, 2558525056, 2566913408, 2575301504, 2583686528, 2592073856, 2600467328, 2608856192, 2617240448, 2625631616, 2634022016, 2642407552, 2650796416, 2659188352, 2667574912, 2675965312, 2684352896, 2692738688, 2701130624, 2709518464, 2717907328, 2726293376, 2734685056, 2743073152, 2751462016, 2759851648, 2768232832, 2776625536, 2785017728, 2793401984, 2801794432, 2810182016, 2818571648, 2826959488, 2835349376, 2843734144, 2852121472, 2860514432, 2868900992, 2877286784, 2885676928, 2894069632, 2902451584, 2910843008, 2919234688, 2927622784, 2936011648, 2944400768, 2952789376, 2961177728, 2969565568, 2977951616, 2986338944, 2994731392, 3003120256, 3011508352, 3019895936, 3028287104, 3036675968, 3045063808, 3053452928, 3061837696, 3070228352, 3078615424, 3087003776, 3095394944, 3103782272, 3112173184, 3120562048, 3128944768, 3137339264, 3145725056, 3154109312, 3162505088, 3170893184, 3179280256, 3187669376, 3196056704, 3204445568, 3212836736, 3221224064, 3229612928, 3238002304, 3246391168, 3254778496, 3263165824, 3271556224, 3279944576, 3288332416, 3296719232, 3305110912, 3313500032, 3321887104, 3330273152, 3338658944, 3347053184, 3355440512, 3363827072, 3372220288, 3380608384, 3388997504, 3397384576, 3405774208, 3414163072, 3422551936, 3430937984, 3439328384, 3447714176, 3456104576, 3464493952, 3472883584, 3481268864, 3489655168, 3498048896, 3506434432, 3514826368, 3523213952, 3531603584, 3539987072, 3548380288, 3556763264, 3565157248, 3573545344, 3581934464, 3590324096, 3598712704, 3607098752, 3615488384, 3623877248, 3632265856, 3640646528, 3649043584, 3657430144, 3665821568, 3674207872, 3682597504, 3690984832, 3699367808, 3707764352, 3716152448, 3724541056, 3732925568, 3741318016, 3749706368, 3758091136, 3766481536, 3774872704, 3783260032, 3791650432, 3800036224, 3808427648, 3816815488, 3825204608, 3833592704, 3841981568, 3850370432, 3858755968, 3867147904, 3875536256, 3883920512, 3892313728, 3900702592, 3909087872, 3917478784, 3925868416, 3934256512, 3942645376, 3951032192, 3959422336, 3967809152, 3976200064, 3984588416, 3992974976, 4001363584, 4009751168, 4018141312, 4026530432, 4034911616, 4043308928, 4051695488, 4060084352, 4068472448, 4076862848, 4085249408, 4093640576, 4102028416, 4110413696, 4118805632, 4127194496, 4135583104, 4143971968, 4152360832, 4160746112, 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