Work fetch and GPUs

Problems with the current work fetch policy

The current work-fetch policy is essentially:

• Do a weighted round-robin simulation, computing overall CPU shortfall
• If there's a shortfall, request work from the project with highest LTD

The scheduler request has a single number "work_req_seconds" indicating the total duration of jobs being requested.

This policy has various problems.

• There's no way for the client to say "I have N idle CPUs, so send me enough jobs to use them all".

And many problems related to GPUs:

• There may be no CPU shortfall, but GPUs are idle; no work will be fetched.

• If a GPU is idle, we should get work from a project that potentially has jobs for it.

• If a project has both CPU and GPU jobs, we may need to tell it to send only GPU (or only CPU) jobs.

• LTD is computed solely on the basis of CPU time used, so it doesn't provide a meaningly comparison between projects that use only GPUs, or between a GPU project and a CPU project.

This document proposes a work-fetch system that solves these problems.

For simplicity, the design assumes that there is only one GPU time (CUDA). It is straightforward to extend the design to handle additional GPU types.

Terminology

A job sent to a client is associated with an app version, which uses some number (possibly fractional) of CPUs and CUDA devices.

• A CPU job is one that uses only CPU.
• A CUDA job is one that uses CUDA (and may use CPU as well).

Scheduler request

New fields in scheduler request message:

double cpu_req_seconds: number of CPU seconds requested

double cuda_req_seconds: number of CUDA seconds requested

double ninstances_cpu: send enough jobs to occupy this many CPUs

double ninstances_cuda: send enough jobs to occupy this many CUDA devs

For compatibility with old servers, the message still has work_req_seconds; this is the max of (cpu,cuda)_req_seconds.

Client

New abstraction: processing resource or PRSC. There are two processing resource types: CPU and CUDA.

Each PRSC has its own

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RESOURCE_WORK_FETCH

base class for the work-fetch policy of a resource derived classes include all RR sim - related data

clear()

called before RR sim

prepare()

called before exists_fetchable_project() sees if there's project to req from for this resource, and caches that

bool exists_fetchable_project()

there's a project we can ask for work for this resource

select_project(priority, char buf)

if the importance of getting work for this resource is P, chooses and returns a PROJECT to request work from, and a string to put in the request message Choose the project for which LTD + expected payoff is largest

values for priority:

DONT_NEED:

no shortfalls

NEED: a shortfall, but no idle devices right now NEED_NOW: idle devices right not

runnable_resource_share()

get_priority()

bool count_towards_share(PROJECT p)

whether to count p's resource share in the total for this rsc

whether we've got a job of this type in last 30 days

add_shortfall(PROJECT, dt)

add x to this project's shortfall, where x = dt*(share - instances used)

double total_share()

total resource share of projects we're counting

accumulate_debt(dt)

for each project p

x = insts of this device used by P's running jobs y = P's share of this device update P's LTD

The following defined in base class:

accumulate_shortfall(dt, i, n)

i = instances in use, n = total instances nidle = n - i max_nidle max= nidle shortfall += dt*(nidle) for each project p for which count_towards_share(p)

add_proj_shortfall(p, dt)

data members:

double shortfall double max_nidle

data per project: (* means save in state file)

double shortfall int last_job*

last time we had a job from this proj using this rsc if the time is within last N days (30?) we assume that the project may possibly have jobs of that type

bool runnable max deficit backoff timer*

how long to wait until ask project for work only for this rsc double this any time we ask only for work for this rsc and get none (maximum 24 hours) clear it when we have a job that uses the rsc

double share

# of instances this project should get based on RS

double long_term_debt*

derived classes:

CPU_WORK_FETCH CUDA_WORK_FETCH

we could eventually subclass this from COPROC_WORK_FETCH

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debt accounting

for each resource type

R.accumulate_debt(dt)

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RR sim

do simulation as current on completion of an interval dt

cpu_work_fetch.accumulate_shortfall(dt) cuda_work_fetch.accumulate_shortfall(dt)

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scheduler request msg double work_req_seconds double cuda_req_seconds bool send_only_cpu bool send_only_cuda double ninstances_cpu double ninstances_cuda

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work fetch

We need to deal w/ situation where there's GPU shortfall

but no projects are supplying GPU work. We don't want an overall backoff from those projects. Solution: maintain separate backoff timer per resource

send_req(p)

switch cpu_work_fetch.priority

case DONT_NEED

set no_cpu in req message

case NEED, NEED_NOW:

work_req_sec = p.cpu_shortfall ncpus_idle = p.max_idle_cpus

switch cuda_work_fetch.priority

case DONT_NEED

set no_cuda in the req message

case NEED, NEED_NOW:

for prior = NEED_NOW, NEED

for each coproc C (in decreasing order of importance) p = C.work_fetch.select_proj(prior, msg);

if p

put msg in req message send_req(p) return

else

p = cpu_work_fetch(prior)

if p

send_req(p) return

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When get scheduler reply

if request.

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scheduler }}}