While I don't know of any tool that provides this information specifically, Percona Server does have a setting (log_slow_verbosity=full) that enables extended statisitics in the slow log along with microsecond granularity. The data does not explicitly include CPU utilization, but it does provide a number of additional statistics about the internals of MySQL and InnoDB that may help you determine whether or not the problem is CPU related or a result of poor optimization.
This is an example of the additional information in the slow log:
# Time: 120114 6:34:33
# User@Host: user[user] @ [10.10.10.10]
# Thread_id: 28313080 Schema: mydb Last_errno: 0 Killed: 0
# Query_time: 0.588882 Lock_time: 0.000068 Rows_sent: 3 Rows_examined: 183839 Rows_affected: 0 Rows_read: 100
# Bytes_sent: 121 Tmp_tables: 0 Tmp_disk_tables: 0 Tmp_table_sizes: 0
# InnoDB_trx_id: 9903E4DB1
# QC_Hit: No Full_scan: No Full_join: No Tmp_table: No Tmp_table_on_disk: No
# Filesort: No Filesort_on_disk: No Merge_passes: 0
# InnoDB_IO_r_ops: 0 InnoDB_IO_r_bytes: 0 InnoDB_IO_r_wait: 0.000000
# InnoDB_rec_lock_wait: 0.000000 InnoDB_queue_wait: 0.000000
# InnoDB_pages_distinct: 11359
Also, pt-query-digest from the Percona Toolkit understands this additional information and will summarize the slow query log for you and produce output, per query, that looks like this:
# Query 1: 0.09 QPS, 0.07x concurrency, ID 0x20112A1CCDBDBA4E at byte 4337645
# Scores: Apdex = 1.00 [1.0], V/M = 0.01
# Query_time sparkline: | ^ |
# Time range: 2012-01-14 06:34:33 to 08:51:57
# Attribute pct total min max avg 95% stddev median
# ============ === ======= ======= ======= ======= ======= ======= =======
# Count 63 775
# Exec time 59 539s 522ms 855ms 695ms 816ms 87ms 640ms
# Lock time 18 60ms 43us 498us 76us 103us 36us 66us
# Rows sent 1 3.15k 0 38 4.17 12.54 4.90 2.90
# Rows examine 22 135.93M 179.38k 179.90k 179.60k 174.27k 0 174.27k
# Rows affecte 0 0 0 0 0 0 0 0
# Rows read 0 3.43k 0 118 4.53 20.43 11.93 0.99
# Bytes sent 1 103.07k 82 576 136.18 246.02 63.85 118.34
# Merge passes 0 0 0 0 0 0 0 0
# Tmp tables 0 0 0 0 0 0 0 0
# Tmp disk tbl 0 0 0 0 0 0 0 0
# Tmp tbl size 0 0 0 0 0 0 0 0
# Query size 5 222.51k 294 294 294 294 0 294
# InnoDB:
# IO r bytes 0 0 0 0 0 0 0 0
# IO r ops 0 0 0 0 0 0 0 0
# IO r wait 0 0 0 0 0 0 0 0
# pages distin 63 8.44M 10.66k 12.72k 11.15k 11.34k 357.67 10.80k
# queue wait 0 0 0 0 0 0 0 0
# rec lock wai 0 0 0 0 0 0 0 0
# String:
# Databases mydb
# Hosts
# InnoDB trxID 9903E4DB1 (1/0%), 9903E4E09 (1/0%)... 773 more
# Last errno 0
# Users user
# Query_time distribution
# 1us
# 10us
# 100us
# 1ms
# 10ms
# 100ms ################################################################
# 1s
# 10s+
# Tables
# SHOW TABLE STATUS FROM `mydb` LIKE 'table'\G
# SHOW CREATE TABLE `mydb`.`table`\G
# EXPLAIN /*!50100 PARTITIONS*/
...followed by the query itself.
I have blogged a bit about using pt-query-digest and other tools for finding performance bottlenecks (and promised more blogging, but haven't gotten around to it yet).
Another tool which may help you is pt-stalk and pt-collect. This will allow you to set a threshold based on a running server variable, such as when the number of concurrently running threads jumps up (Threads_running) and then collect a wealth of data about the running system, including cpu, I/O, MySQL statistics, the running processlist, etc to give you the ability to perform a thorough post-mortem.
The additional statistics are only available in Percona Server, but these tools will all work with MySQL GA.