cuda2llm-trained / full_run.log
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=== SYSTEM ===
2026-07-06T00:33:20+00:00
NVIDIA RTX A4000, 16376 MiB, 550.144.03
Build cuda_12.4.r12.4/compiler.34097967_0
=== CHAPTER CHECKS ===
--- code/ch02 ---
nvcc -O3 -arch=native -lm -o hello hello.cu
nvcc -O3 -arch=native -lm -o vector_add vector_add.cu
code/ch02/hello
Hello from block 0, thread 0
Hello from block 0, thread 1
Hello from block 0, thread 2
Hello from block 0, thread 3
Hello from block 1, thread 0
Hello from block 1, thread 1
Hello from block 1, thread 2
Hello from block 1, thread 3
code/ch02/vector_add
OK vector_add
--- code/ch03 ---
nvcc -O3 -arch=native -lm -o indices indices.cu
nvcc -O3 -arch=native -lm -o matrix_add matrix_add.cu
nvcc -O3 -arch=native -lm -o grid_stride grid_stride.cu
code/ch03/grid_stride
OK grid_stride
code/ch03/indices
block (0,1) thread (0,0) -> row 2 col 0 idx 16
block (0,1) thread (1,0) -> row 2 col 1 idx 17
block (0,1) thread (2,0) -> row 2 col 2 idx 18
block (0,1) thread (3,0) -> row 2 col 3 idx 19
block (0,1) thread (0,1) -> row 3 col 0 idx 24
block (0,1) thread (1,1) -> row 3 col 1 idx 25
block (0,1) thread (2,1) -> row 3 col 2 idx 26
block (0,1) thread (3,1) -> row 3 col 3 idx 27
block (1,1) thread (0,0) -> row 2 col 4 idx 20
block (1,1) thread (1,0) -> row 2 col 5 idx 21
block (1,1) thread (2,0) -> row 2 col 6 idx 22
block (1,1) thread (3,0) -> row 2 col 7 idx 23
block (1,1) thread (0,1) -> row 3 col 4 idx 28
block (1,1) thread (1,1) -> row 3 col 5 idx 29
block (1,1) thread (2,1) -> row 3 col 6 idx 30
block (1,1) thread (3,1) -> row 3 col 7 idx 31
block (1,0) thread (0,0) -> row 0 col 4 idx 4
block (1,0) thread (1,0) -> row 0 col 5 idx 5
block (1,0) thread (2,0) -> row 0 col 6 idx 6
block (1,0) thread (3,0) -> row 0 col 7 idx 7
block (1,0) thread (0,1) -> row 1 col 4 idx 12
block (1,0) thread (1,1) -> row 1 col 5 idx 13
block (1,0) thread (2,1) -> row 1 col 6 idx 14
block (1,0) thread (3,1) -> row 1 col 7 idx 15
block (0,0) thread (0,0) -> row 0 col 0 idx 0
block (0,0) thread (1,0) -> row 0 col 1 idx 1
block (0,0) thread (2,0) -> row 0 col 2 idx 2
block (0,0) thread (3,0) -> row 0 col 3 idx 3
block (0,0) thread (0,1) -> row 1 col 0 idx 8
block (0,0) thread (1,1) -> row 1 col 1 idx 9
block (0,0) thread (2,1) -> row 1 col 2 idx 10
block (0,0) thread (3,1) -> row 1 col 3 idx 11
code/ch03/matrix_add
OK matrix_add
--- code/ch04 ---
nvcc -O3 -arch=native -lm -o bandwidth bandwidth.cu
nvcc -O3 -arch=native -lm -o coalesce coalesce.cu
code/ch04/bandwidth
buffer size: 134217728 floats (537 MB each)
traffic per launch (read + write): 1074 MB
average time over 10 launches: 2.725 ms
achieved bandwidth: 394.0 GB/s
OK bandwidth
code/ch04/coalesce
matrix: 8192 x 8192 floats (268 MB read + 268 MB written per pass)
row-order (coalesced): 1.366 ms (392.9 GB/s)
column-order (strided) : 5.375 ms (99.9 GB/s)
strided / coalesced slowdown: 3.9x
OK coalesce
--- code/ch05 ---
nvcc -O3 -arch=native -lm -o transpose transpose.cu
nvcc -O3 -arch=native -lm -o race race.cu
code/ch05/race
RACE (may vary): reverse_broken: 2046720 of 4194304 elements wrong
a data race is undefined behavior: the count above can change
from run to run, and 0 wrong is luck, not correctness
OK race_fixed
code/ch05/transpose
transpose: 4096 x 2048 floats (67.1 MB moved per run)
OK transpose_naive
OK transpose_tiled
OK transpose_padded
kernel ms GB/s speedup
transpose_naive 0.533 125.9 1.00x
transpose_tiled 0.277 242.1 1.92x
transpose_padded 0.194 346.3 2.75x
--- code/ch06 ---
nvcc -O3 -arch=native -lm histogram.cu -o histogram
nvcc -O3 -arch=native -lm reduce.cu -o reduce
code/ch06/histogram
histogram (random bytes): 3.298 ms
OK histogram
histogram (one hot bin): 6.743 ms (2.0x slower)
OK histogram_worst_case
code/ch06/reduce
CPU (double) sum: -151.5765
reduce_atomic: sum -151.6804 32.582 ms
reduce_tree: sum -151.5632 0.350 ms
reduce_shuffle: sum -151.5666 0.218 ms
OK reduce_atomic
OK reduce_tree
OK reduce_shuffle
--- code/ch07 ---
nvcc -O3 -arch=native -lm silent_fail.cu -o silent_fail
nvcc -O3 -arch=native -lm timing.cu -o timing
code/ch07/silent_fail
--- part 1: illegal launch, no error checking ---
kernel "ran" in 0.1864 ms (says the host clock)
out[0] = 0.000000, expected 1.251290 <- the kernel never ran
--- part 2: same launch, but now we ask ---
cudaGetLastError says: invalid configuration argument
--- part 3: legal launch, checked, verified ---
OK silent_fail_fixed
code/ch07/timing
WRONG (host clock, no sync): 0.0034 ms
RIGHT (events, warmup, avg of 10): 0.3461 ms = 387.8 GB/s
OK timing
--- code/ch08 ---
nvcc -O3 -arch=native -lm -o matmul_naive matmul_naive.cu
code/ch08/matmul_naive
matmul: C(1024,1024) = A(1024,1024) @ B(1024,1024), 2.15 GFLOP per run
computing CPU reference (single core; this takes a few seconds)...
OK matmul_naive
CPU: 4628.6 ms 0.46 GFLOP/s
GPU: 1.851 ms 1160.4 GFLOP/s
speedup: 2501.2x
--- code/ch09 ---
nvcc -O3 -arch=native -lm -o matmul_ladder matmul_ladder.cu
nvcc -O3 -arch=native -lm -o matmul_forward matmul_forward.cu
code/ch09/matmul_forward
computing CPU references (a few seconds)...
matmul_forward: N=8192 C=384 OC=1152 bias=yes
OK matmul_forward
matmul_forward: 4.879 ms, 1485.4 GFLOP/s
matmul_forward_ragged: N=100 C=65 OC=37 bias=NULL
OK matmul_forward_ragged
code/ch09/matmul_ladder
matmul ladder: C(1024,1024) = A(1024,1024) @ B(1024,1024), 2.15 GFLOP per run
computing CPU reference (a few seconds)...
OK matmul_naive
OK matmul_tiled
OK matmul_regtile
kernel ms GFLOP/s speedup
matmul_naive 1.955 1098.6 1.00x
matmul_tiled 1.577 1361.7 1.24x
matmul_regtile 0.370 5807.6 5.29x
--- code/ch10 ---
nvcc -O3 -arch=native -lm softmax.cu -o softmax
nvcc -O3 -arch=native -lm reduce_row.cu -o reduce_row
code/ch10/reduce_row
OK rowmax
OK rowsum
code/ch10/softmax
one row of large scores through both kernels (a demonstration):
logits: 101.3 99.1 102.7 12.0 100.0 103.9 97.2 100.8
naive: nan nan nan 0.000000 nan nan nan nan
safe: 0.051216 0.005675 0.207688 0.000000 0.013958 0.689551 0.000849 0.031064
OK softmax_v65
softmax_v65: N=8192 V=65 0.046 ms ~229 GB/s effective
OK softmax_v1000
softmax_v1000: N=8192 V=1000 0.173 ms ~948 GB/s effective
OK softmax_rowsum
--- code/ch11 ---
nvcc -O3 -arch=native -lm layernorm.cu -o layernorm
nvcc -O3 -arch=native -lm gelu.cu -o gelu
code/ch11/gelu
x gelu(x)
-2 -0.0454
-1 -0.1588
0 0.0000
1 0.8412
2 1.9546
OK gelu
code/ch11/layernorm
N=8192 rows, C=384 channels
OK layernorm_out
OK layernorm_mean
OK layernorm_rstd
N=1000 rows, C=100 channels
OK layernorm_ragged
--- code/ch12 ---
nvcc -O3 -arch=native -lm encoder.cu -o encoder
nvcc -O3 -arch=native -lm crossentropy.cu -o crossentropy
code/ch12/crossentropy
OK softmax
OK crossentropy
uniform logits: mean loss 4.174387, expected ln(65) = 4.174387
OK uniform_loss_4.17
code/ch12/encoder
OK encoder
--- code/ch13 ---
nvcc -O3 -arch=native -lm attention.cu -o attention
code/ch13/attention
OK attention_out
OK attention_att
OK attention_causal
--- code/ch16 ---
cc -O2 -lm -o toy_backprop toy_backprop.c
code/ch16/toy_backprop
forward: z = 7.0, y = 49.0
backward: dx = 42.0, dw = 28.0, db = 14.0
finite difference dx ~= 42.002
OK toy_backprop
=== GPT BUILD ===
rm -f prepare_data train_gpt generate_gpt grad_check
cc -O2 -lm -o prepare_data prepare_data.c
nvcc -O3 -arch=native -lm -o train_gpt train_gpt.cu
nvcc -O3 -arch=native -lm -o generate_gpt generate_gpt.cu
nvcc -O3 -arch=native -lm -o grad_check grad_check.cu
=== DATA ===
curl -L -o input.txt https://raw.githubusercontent.com/karpathy/char-rnn/master/data/tinyshakespeare/input.txt
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0 100 1089k 100 1089k 0 0 4798k 0 --:--:-- --:--:-- --:--:-- 4819k
tokens: 1115394 | vocab: 65 | train: 1003854 | val: 111540
=== GRAD CHECK ===
analytic -0.074804
numerical -0.074863
diff 0.000060
OK grad_check_wte0
=== TRAIN 5000 ===
parameters: 10770816
step 1 | loss 4.2383 | lr 0.000010 | 7300 tok/s
step 100 | loss 2.4751 | lr 0.001000 | 7039 tok/s
step 200 | loss 2.3741 | lr 0.000999 | 6967 tok/s
val 250 | loss 2.2469
step 300 | loss 2.1620 | lr 0.000996 | 7033 tok/s
step 400 | loss 1.8983 | lr 0.000992 | 7017 tok/s
step 500 | loss 1.7598 | lr 0.000985 | 7035 tok/s
val 500 | loss 1.9397
step 600 | loss 1.7097 | lr 0.000977 | 7024 tok/s
step 700 | loss 1.7504 | lr 0.000967 | 7036 tok/s
val 750 | loss 1.8425
step 800 | loss 1.6235 | lr 0.000955 | 7022 tok/s
step 900 | loss 1.5730 | lr 0.000942 | 7052 tok/s
step 1000 | loss 1.6028 | lr 0.000927 | 7029 tok/s
val 1000 | loss 1.7558
saved model.bin at step 1000
step 1100 | loss 1.6541 | lr 0.000911 | 7029 tok/s
step 1200 | loss 1.6146 | lr 0.000893 | 7051 tok/s
val 1250 | loss 1.6679
step 1300 | loss 1.4642 | lr 0.000873 | 7035 tok/s
step 1400 | loss 1.3288 | lr 0.000853 | 7034 tok/s
step 1500 | loss 1.3054 | lr 0.000831 | 7043 tok/s
val 1500 | loss 1.6317
step 1600 | loss 1.3982 | lr 0.000807 | 7063 tok/s
step 1700 | loss 1.3385 | lr 0.000783 | 7052 tok/s
val 1750 | loss 1.6163
step 1800 | loss 1.2542 | lr 0.000758 | 7047 tok/s
step 1900 | loss 1.3436 | lr 0.000732 | 7050 tok/s
step 2000 | loss 1.2770 | lr 0.000705 | 7062 tok/s
val 2000 | loss 1.5911
saved model.bin at step 2000
step 2100 | loss 1.2688 | lr 0.000678 | 7052 tok/s
step 2200 | loss 1.1882 | lr 0.000650 | 7042 tok/s
val 2250 | loss 1.6044
step 2300 | loss 1.3317 | lr 0.000622 | 7046 tok/s
step 2400 | loss 1.1211 | lr 0.000593 | 7036 tok/s
step 2500 | loss 1.2006 | lr 0.000564 | 7059 tok/s
val 2500 | loss 1.6112
step 2600 | loss 1.1568 | lr 0.000536 | 7065 tok/s
step 2700 | loss 1.2186 | lr 0.000507 | 7067 tok/s
val 2750 | loss 1.6321
step 2800 | loss 1.1401 | lr 0.000478 | 7069 tok/s
step 2900 | loss 1.0421 | lr 0.000450 | 7064 tok/s
step 3000 | loss 1.1062 | lr 0.000422 | 7057 tok/s
val 3000 | loss 1.6381
saved model.bin at step 3000
step 3100 | loss 0.9624 | lr 0.000395 | 7069 tok/s
step 3200 | loss 1.0200 | lr 0.000368 | 7073 tok/s
val 3250 | loss 1.6753
step 3300 | loss 1.0242 | lr 0.000342 | 7089 tok/s
step 3400 | loss 1.0527 | lr 0.000317 | 7055 tok/s
step 3500 | loss 0.9729 | lr 0.000293 | 7063 tok/s
val 3500 | loss 1.7316
step 3600 | loss 0.9506 | lr 0.000269 | 7077 tok/s
step 3700 | loss 0.9488 | lr 0.000247 | 7067 tok/s
val 3750 | loss 1.7931
step 3800 | loss 0.9607 | lr 0.000227 | 7055 tok/s
step 3900 | loss 0.9824 | lr 0.000207 | 7056 tok/s
step 4000 | loss 0.7658 | lr 0.000189 | 7031 tok/s
val 4000 | loss 1.8825
saved model.bin at step 4000
step 4100 | loss 0.8902 | lr 0.000173 | 7044 tok/s
step 4200 | loss 0.7832 | lr 0.000158 | 7047 tok/s
val 4250 | loss 1.9381
step 4300 | loss 0.8469 | lr 0.000145 | 7036 tok/s
step 4400 | loss 0.8653 | lr 0.000133 | 7053 tok/s
step 4500 | loss 0.8695 | lr 0.000123 | 7035 tok/s
val 4500 | loss 1.9576
step 4600 | loss 0.7353 | lr 0.000115 | 7048 tok/s
step 4700 | loss 0.7704 | lr 0.000108 | 7046 tok/s
val 4750 | loss 1.9924
step 4800 | loss 0.7446 | lr 0.000104 | 7032 tok/s
step 4900 | loss 0.8131 | lr 0.000101 | 7042 tok/s
step 5000 | loss 0.7931 | lr 0.000100 | 7054 tok/s
val 5000 | loss 2.0483
saved model.bin at step 5000
=== GENERATE ROMEO ===
ROMEO:
Ay not sustom's master and by earor-woo's love;
She damned life, lest have had some removed,
Lest in neither slander man, and might have
Because the moon his commission.
MARCIUS:
No, I'll consent the choler is prince:
I am gone to great the last of my master;
That's smules not put to my counsel.
LARTIUS:
He'll down away; alas, my liege, may stand
And in the truth of one sons with that for night
But upon'sy. Let thou go;
How sometimes thee on the ground the vault?
Though thy wife will then to thee to thine,
And doth me, thy force should thee from thy brother
As thou didst uncontent? I think thee, that would ens
Of gracious that here were most under his pleasing
pay a wordfather, a mother; a boote ardone
And this one in so to be a child, and so meek
To lie in; and so, as the which I do ha
=== GENERATE JULIET ===
JULIET:
And fearn gather nothing by thy lance.
Is my daughter's most reason can strengthen's stand
My separance up and hereport of their children,
My mildness and constant seize in purge
With informal enrage, that the habit ours.
Say thou never have me once what I have:
Not hear then beat his; 'twere thy toother such
And see the gates that which he can say.
KING EDWARD IV:
The gods be thereof there! O thee, climbs:
This is there: 'for thou re's more there's service:
'Tis thou there?
Why, villain, if thou know'st this noble armed,
It must are the alive. But what is this?
GLOUCESTER:
It should be, there's no consort or charge.
YORK:
At what command?
CLARENCE:
It is. For that docts but loss this thought of thee,
As doubt the truth of the whole head.
GLOUCESTER:
Your brother is and Polixenes,
Ho
=== ARTIFACTS ===
-rw-r--r-- 1 root root 124M Jul 6 02:12 model.bin
-rw-r--r-- 1 root root 3.9M Jul 6 00:34 train.bin
-rw-r--r-- 1 root root 436K Jul 6 00:34 val.bin
-rw-r--r-- 1 root root 73 Jul 6 00:34 vocab.bin
75eb8311e2bdec22b0c0e40084fb39fb1ed190662d3cd51f26e9f4b37ee06691 model.bin
464eb51d66b5b643889064b82c75607e2d756df11ec960e5e6aaaf03c71734be vocab.bin
a3f591a5c0dfa7f54a2ec0ab39c4561d6475f1af28264f38076932ca425d5037 train.bin
836220b36a012c19cd285816001700117edef4f8e1098130b234d4b8fa766d86 val.bin
=== DONE ===
2026-07-06T02:12:17+00:00