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Updating compute budget on JURECA/JSC (hwai) to the active one #148

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Merged
neginraoof merged 3 commits into from
Dec 22, 2025
Merged

Updating compute budget on JURECA/JSC (hwai) to the active one #148

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5b59fa3
Update simple_jureca.sbatch
JeniaJitsev Dec 22, 2025
93b19d4
Update process_shards_jureca.sbatch
JeniaJitsev Dec 22, 2025
84b34a5
Update SETUP_JURECA.md
JeniaJitsev Dec 22, 2025
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2 changes: 1 addition & 1 deletion eval/distributed/SETUP_JURECA.md
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Expand Up @@ -88,7 +88,7 @@ huggingface-cli download mlfoundations-dev/evalset_2870 --repo-type dataset
huggingface-cli download open-thoughts/OpenThinker-7B

# Request an interactive node for testing
salloc --nodes=1 --ntasks-per-node=1 --gres=gpu:1 --cpus-per-task=12 -p dc-hwai -A westai0007
salloc --nodes=1 --ntasks-per-node=1 --gres=gpu:1 --cpus-per-task=12 -p dc-hwai -A westai0066

# Verify GPU is available
srun bash -c 'nvidia-smi'
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4 changes: 2 additions & 2 deletions eval/distributed/process_shards_jureca.sbatch
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Expand Up @@ -5,7 +5,7 @@
#SBATCH --gres=gpu:1
#SBATCH --time=01:00:00
#SBATCH --cpus-per-task=12
#SBATCH --account=westai0007
#SBATCH --account=westai0066
#SBATCH --partition=dc-hwai

# ENVIRONMENT VARIABLES
Expand All @@ -23,4 +23,4 @@ export OUTPUT_DATASET="$DCFT_DATA/evalchemy_results/${MODEL_NAME##*--}_${INPUT_D

# RUN SHARDED INFERENCE
srun echo -e "GLOBAL_SIZE: ${GLOBAL_SIZE}\nRANK: ${RANK}\nMODEL: ${MODEL_NAME}\nINPUT_DATASET: ${INPUT_DATASET}\nOUTPUT_DATASET: ${OUTPUT_DATASET}"
srun python $EVALCHEMY/eval/distributed/process_shard.py --global_size ${GLOBAL_SIZE} --rank ${RANK} --input_dataset ${INPUT_DATASET} --model_name ${MODEL_NAME} --output_dataset ${OUTPUT_DATASET}
srun python $EVALCHEMY/eval/distributed/process_shard.py --global_size ${GLOBAL_SIZE} --rank ${RANK} --input_dataset ${INPUT_DATASET} --model_name ${MODEL_NAME} --output_dataset ${OUTPUT_DATASET}
4 changes: 2 additions & 2 deletions eval/distributed/simple_jureca.sbatch
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Expand Up @@ -4,7 +4,7 @@
#SBATCH --gres=gpu:4
#SBATCH --time={time_limit}
#SBATCH --cpus-per-task=12
#SBATCH --account=westai0007
#SBATCH --account=westai0066
#SBATCH --partition=dc-hwai
#SBATCH --job-name={job_name}
#SBATCH --output={logs_dir}/%x_%j.out
Expand All @@ -25,4 +25,4 @@ OUTPUT_DATASET={output_dataset}

# RUN SHARDED INFERENCE
srun --output={logs_dir}/%x_%j_%t.out bash -c 'echo -e "GLOBAL_SIZE: ${SLURM_STEP_NUM_TASKS}\nRANK: ${SLURM_PROCID}\nMODEL: '$MODEL_NAME'\nINPUT_DATASET: '$INPUT_DATASET'\nOUTPUT_DATASET: '$OUTPUT_DATASET'"'
srun --output={logs_dir}/%x_%j_%t.out bash -c 'CUDA_VISIBLE_DEVICES=${SLURM_LOCALID} python $EVALCHEMY/eval/distributed/process_shard.py --global_size ${SLURM_STEP_NUM_TASKS} --rank ${SLURM_PROCID} --input_dataset '${INPUT_DATASET}' --model_name '${MODEL_NAME}' --output_dataset '${OUTPUT_DATASET}''
srun --output={logs_dir}/%x_%j_%t.out bash -c 'CUDA_VISIBLE_DEVICES=${SLURM_LOCALID} python $EVALCHEMY/eval/distributed/process_shard.py --global_size ${SLURM_STEP_NUM_TASKS} --rank ${SLURM_PROCID} --input_dataset '${INPUT_DATASET}' --model_name '${MODEL_NAME}' --output_dataset '${OUTPUT_DATASET}''