Avocode 4 12 0 64 bit

OpponentEloDiffResultsScoreLOSPerf– Stockfish 15 64-bit 4CPU3622+13−13(+164)6.5 − 13.5(+0−7=13)32.5%6.5 / 200.0%+53– Stockfish 14 64-bit 4CPU3621+13−13(+163)5.5 − 14.5(+0−9=11)27.5%5.5 / 200.0%+14– Dragon by Komodo 3.1 64-bit 4CPU3616+14−14(+158)5 − 15(+0−10=10)25.0%5.0 / 200.0%−8– Fat Fritz 2 64-bit 4CPU3601+10−10(+143)6.5 − 13.5(+0−7=13)32.5%6.5 / 200.0%+32– Berserk 10 64-bit 4CPU3567+13−13(+109)6 − 14(+0−8=12)30.0%6.0 / 200.0%−18– Revenge 3.0 64-bit 4CPU3558+9−9(+100)6.5 − 13.5(+1−8=11)32.5%6.5 / 200.0%−15– Ethereal 13.75 64-bit 4CPU3554+12−12(+96)6.5 − 13.5(+0−7=13)32.5%6.5 / 200.0%−14– Koivisto 8.0 64-bit 4CPU3551+11−11(+93)7 − 13(+0−6=14)35.0%7.0 / 200.0%−2– SlowChess Blitz 2.9 64-bit 4CPU3545+9−9(+87)8.5 − 11.5(+0−3=17)42.5%8.5 / 200.0%+41– Clover 5.0 64-bit 4CPU3544+17−17(+86)12 − 20(+0−8=24)37.5%12.0 / 320.0%+9– Deep Sjeng 3.6 a16 64-bit 4CPU3544+16−16(+86)12 − 20(+0−8=24)37.5%12.0 / 320.0%+9– RubiChess 20220813 64-bit 4CPU3530+15−15(+72)7 − 13(+0−6=14)35.0%7.0 / 200.0%−20– rofChade 3.0 64-bit 4CPU3526+10−10(+68)7 − 13(+0−6=14)35.0%7.0 / 200.0%−24– Clover 4.0 64-bit 4CPU3525+16−16(+67)11 − 19(+0−8=22)36.7%11.0 / 300.0%−16– Minic 3.32 64-bit 4CPU3520+14−14(+62)8.5 − 15.5(+0−7=17)35.4%8.5 / 240.0%−28– Minic 3.30 64-bit 4CPU3515+14−14(+57)6.5 − 13.5(+0−7=13)32.5%6.5 / 200.0%−52– Caissa 1.8 64-bit 4CPU3513+17−17(+55)11 − 15(+0−4=22)42.3%11.0 / 260.0%+8– Seer 2.5.0 64-bit 4CPU3510+13−13(+52)9.5 − 10.5(+1−2=17)47.5%9.5 / 200.0%+38– Carp 3.0.0 64-bit 4CPU3501+16−16(+43)10.5 − 11.5(+0−1=21)47.7%10.5 / 220.0%+29– Arasan 23.4 64-bit 4CPU3499+13−13(+41)8.5 − 11.5(+0−3=17)42.5%8.5 / 200.0%−4– Uralochka 3.38c 64-bit 4CPU3493+15−15(+35)10 − 10(+2−2=16)50.0%10.0 / 200.0%+35– Rebel 15.1a 64-bit 4CPU3490+16−16(+32)9 − 11(+0−2=18)45.0%9.0 / 200.1%+4– Arasan 23.5 64-bit 4CPU3488+15−15(+30)10.5 − 11.5(+1−2=19)47.7%10.5 / 220.2%+17– Igel 3.1.0 64-bit 4CPU3484+12−12(+26)9.5 − 10.5(+0−1=19)47.5%9.5 / 200.3%+13– Black Marlin 7.0 64-bit 4CPU3466+14−14(+8)8.5 − 11.5(+1−4=15)42.5%8.5 / 2018.7%−41– Houdini 6 64-bit 4CPU3456+7−7(−2)9 − 11(+1−3=16)45.0%9.0 / 2060.1%−31– Velvet 5.1.0 64-bit 4CPU3454+17−17(−4)16.5 − 13.5(+7−4=19)55.0%16.5 / 3063.2%+29– Marvin 6.1.0 64-bit 4CPU3448+15−15(−10)11.5 − 12.5(+0−1=23)47.9%11.5 / 2482.7%−20– Wasp 6.00 64-bit 4CPU3440+15−15(−18)12.5 − 7.5(+5−0=15)62.5%12.5 / 2096.4%+55– Nemorino 6.05 64-bit 4CPU3432+16−16(−26)10 − 10(+3−3=14)50.0%10.0 / 2099.2%−26– Booot 7.0 64-bit 4CPU3428+16−16(−30)10 − 10(+2−2=16)50.0%10.0 / 2099.7%−33– Velvet 4.1.0 64-bit 4CPU3423+15−15(−35)11 − 9(+4−2=14)55.0%11.0 / 20100.0%−4– Mantissa 3.7.2 64-bit 4CPU3381+15−15(−77)12 − 8(+4−0=16)60.0%12.0 / 20100.0%−17– Marvin 6.0.0 64-bit 4CPU3377+16−16(−81)11 − 9(+2−0=18)55.0%11.0 / 20100.0%−53– Expositor 2BR17 64-bit 4CPU3376+16−16(−82)12.5 − 7.5(+6−1=13)62.5%12.5 / 20100.0%0– Counter 5.0 64-bit 4CPU3373+18−18(−85)14.5 − 9.5(+7−2=15)60.4%14.5 / 24100.0%−17– Smallbrain 6.0 64-bit 4CPU3370+16−16(−88)13.5 − 10.5(+3−0=21)56.3%13.5 / 24100.0%−52– Stash 34.0 64-bit 4CPU3364+18−18(−94)16.5 − 7.5(+10−1=13)68.8%16.5 / 24100.0%+28– Drofa 4.0.0 64-bit 4CPU3318+20−20(−140)15 − 3(+12−0=6)83.3%15.0 / 18100.0%+102– Winter 1.0 64-bit 4CPU3306+18−18(−152)12.5 − 3.5(+9−0=7)78.1%12.5 / 16100.0%+40– Drofa 3.3.22 64-bit 4CPU3300+21−21(−158)13.5 − 6.5(+7−0=13)67.5%13.5 / 20100.0%−47

Happy Gecko Common Specs ARM Cortex-M0+ CPU platform25 MHzUp to 64 kB FlashUp to 8 kB RAM131 μA/MHz in Active Mode (EM0)0.9 μA sleep with RTC and RAM retentionAutonomous peripherals in sleep DMA and peripheral reflex systemUSART, I²C, SPI, and USBUp to 35 General Purpose I/O Pins-40 °C to +105 °C operation range1.98 V to 3.8 V single power supply Packages:24-pin QFN (7 mm x 7 mm)32-pin QFN (6 mm x 6 mm)36-pin QFN (5 mm x 5 mm) Select Columns Part Number MHz Flash RAM Dig I/O Pins 5 Volt Tolerant ADC 1 DAC USB Cap Sense LCD Temp Sensor Timers (16-bit) AES-128 AES-256 ECC SHA-1 SHA-2 RSA-2048 UART USART SPI I2C I2S EMIF RTC Comparators Vdd (min) Vdd (max) Package Type Package Size (mm) Internal Osc. Debug Interface Cryptography New --> EFM32HG108F64G-QFN24 Buy | --> Sample Dev Kit 25 64 8 17 — — 3 3 2 2 1 1 0 1 1.98 3.8 QFN24 5x5 ±2% MTB; SW New --> EFM32HG110F64G-QFN24 Buy | --> Sample Dev Kit 25 64 8 17 12-bit, 2-ch., 1 Msps — 3 3 2 2 1 1 0 1 1.98 3.8 QFN24 5x5 ±2% MTB; SW AES-128 New --> EFM32HG210F64G-QFN32 Buy | --> Sample Dev Kit 25 64 8 24 12-bit, 4-ch., 1 Msps — 3 3 2 2 1 1 0 1 1.98 3.8 QFN32 6x6 ±2% MTB; SW AES-128 New --> EFM32HG222F32G-QFP48 Buy | --> Sample Dev Kit 25 32 4 37 12-bit, 4-ch., 1 Msps — 3 3 2 2 1 1 0 1 1.98 3.8 QFP48 7x7 ±2% MTB; SW AES-128 New --> EFM32HG222F64G-QFP48 Buy | --> Sample Dev Kit 25 64 8 37 12-bit, 4-ch., 1 Msps — 3 3 2 2 1 1 0 1 1.98 3.8 QFP48 7x7 ±2% MTB; SW AES-128 New --> EFM32HG222F64N-QFP48 Buy | --> Dev Kit 25 64 8 37 12-bit, 4-ch., 1 Msps — 3 3 2 2 1 1 0 1 1.98 3.8 QFP48 7x7 ±2% MTB; SW AES-128 New --> EFM32HG310F64G-QFN32 Buy | --> Sample Dev Kit 25 64 8 22 12-bit, 4-ch., 1 Msps — 3 3

Sponsored ContentThis sponsored post features a product relevant to our readers while meeting our editorial guidelines for being objective and educational.In today’s tutorial I’m going to introduce you to Avocode, developed by the “eleven brave men and one brave woman” of Source and recently released in the form of version 1.0. Avocode is an application which allows you to work with .psd and .sketch files, moving from design to code, without even opening Photoshop or Sketch.We covered Avocode a few months ago, but back then it was still in beta and has since undergone some serious feature overhauls. This tutorial will show you how to work with the Avocode desktop application and introduce the new features. Part 1. Getting StartedIn this part of the tutorial I’ll demonstrate how to get setup with Avocode, create projects, upload Photoshop and Sketch files, then work with those files in the Avocode desktop application. Part 2. Exporting CodeIn this video I’ll show you how to generate CSS (along with Sass and Compass) directly from your Photoshop and Sketch files. We’ll also look at some shortcuts and a ton of other helpful features. Let’s get started! Useful Resourcesavocode.com@avocode on TwitterAvocode Stories on Medium

And 64-bit result (L) is obtained. Second, the multiplication is performed with lower 32-bit of 64-bit operands ( A [ 7 ∼ 4 ] , B [ 7 ∼ 4 ] ) and 64-bit result (H) is obtained. Third, XOR operation is performed between the upper part and the lower part of the A and B, respectively. Values are multiplied and output the final result (M). The L, H, and M are XORed together and stored in M, again. Lastly, shifted H ( H ≪ 64 ), shifted M ( M ≪ 32 ) and L are XORed and the final 128-bit result (C) is obtained.Karatsuba algorithm needs a buffer to store intermediate results of each operation. In the Block Comb method proposed by Seo and Kim, the size of intermediate results is over than given size of general purpose registers. For this reason, the part of intermediate result should be stored in STACK. However, accessing to STACK memory (i.e., 2 clock cycles) requires high-overheads than register accesses (i.e., 1 clock cycle). The proposed method uses eight more registers to maintain the intermediate result. For the register optimized version, the intermediate result is stored in STACK memory.In Algorithm 2, the proposed implementation does not reserve the intermediate result of the Karatsuba calculation, such as L, H, and M, in the STACK. Instead, only values needed for the following operation are stored using the K 0 to K 7 registers. When the 128-bit result (C) and the 64-bit intermediate result (M) are divided into 8-bit units, it can be expressed as ( C [ 0 ] , C [ 1 ] , . . . , C [ 15 ] ) and ( M [ 0 ] , M [ 1 ] , . . . , M [ 8 ] ), respectively. Among them, C [ 0 ∼ 3 ] and C [ 12 ∼ 15 ] store the upper 32-bit multiplication result and the lower 32-bit multiplication result.The result from C [ 4 ] to C [ 11 ] is XORed with the M. The final result of C

The example above, these will be: d7ce56a3 566656f3.Let’s reverse the order of bytes in each 4-byte sequences and form two 32-bit integer numbers: a356ced7 f3566656.Together these two sequences form a 64-bit integer number: a356ced7f3566656.This number in the binary format will look as following:0xA356CED7F3566656 = 1010001101010110110011101101011111110011010101100110011001010110Let’s divide the 64-bit value into groups of 5-bit each starting from least significant bits (from right to left):there will be 12 groups 5-bit each, and the last group will have remaining 4-bit.Each 5-bit group can be represented by a 5-bit integer number in the 0-31 range:1010 00110 10101 10110 01110 11010 11111 11001 10101 01100 11001 10010 10110 10 6 21 22 14 26 31 25 21 12 25 18 22Finally, we are going to encode each 5-bit number into a single character using this lookup table:'0','1','2','3','4','5','6','7','8','9','a','b','c','d','f','g','h','j','k','m','n','p','q','r','s','t','u','v','w','x','y','z'Here is a final result, 13-character string, used in Oracle as SQL_ID: 10 6 21 22 14 26 31 25 21 12 25 18 22 a 6 p q f u z t p c t k qSQL_ID = 'a6pqfuztpctkq'Let’s check that with the following SQL and results in Figure 3.select ADDRESS, SQL_ID, HASH_VALUE, to_char(HASH_VALUE,'FMXXXXXXXX') HASH_VALUE_HEXfrom v$sqlwhere sql_text='select 0 from dual';Let’s make few practical conclusions.The possibility of SQL_ID collisions is significantly lower (about 4 billion times lower) than for HASH_VALUE.That means much stronger one-to-one relationship between SQL text and SQL_ID.Therefore, the same SQL_ID means the same SQL text.It no longer matters if they were on different databases, different versions, or different platforms.In this case, same text means that both