Caladan is a system that enables servers in datacenters to simultaneously provide low tail latency and high CPU efficiency, by rapidly reallocating cores across applications.

For any questions about Caladan, please email [email protected].

1. Clone the Caladan repository.

2. Install dependencies.

sudo apt install make gcc cmake pkg-config libnl-3-dev libnl-route-3-dev libnuma-dev uuid-dev libssl-dev libaio-dev libcunit1-dev libclang-dev

3. Set up submodules (e.g., DPDK, SPDK, and rdma-core).

make submodules

4. Build the scheduler (IOKernel), the Caladan runtime, and Ksched and perform some machine setup. Before building, set the parameters in build/config (e.g., CONFIG_SPDK=y to use storage, CONFIG_DIRECTPATH=y to use directpath, and the MLX4 or MLX5 flags to use MLX4 or MLX5 NICs, respectively, ). To enable debugging, set CONFIG_DEBUG=y before building.

make clean && make
pushd ksched
make clean && make
popd
sudo ./scripts/setup_machine.sh

5. Install Rust and build a synthetic client-server application.

curl https://sh.rustup.rs -sSf | sh
rustup default nightly

cd apps/synthetic
cargo clean
cargo update
cargo build --release

6. Run the synthetic application with a client and server. The client sends requests to the server, which performs a specified amount of fake work (e.g., computing square roots for 10us), before responding.

On the server:

sudo ./iokerneld
./apps/synthetic/target/release/synthetic 192.168.1.3:5000 --config server.config --mode spawner-server

On the client:

sudo ./iokerneld
./apps/synthetic/target/release/synthetic 192.168.1.3:5000 --config client.config --mode runtime-client

This code has been tested most thoroughly on Ubuntu 18.04 with kernel 5.2.0 and Ubuntu 20.04 with kernel 5.4.0.

This code has been tested with Intel 82599ES 10 Gbits/s NICs, Mellanox ConnectX-3 Pro 10 Gbits/s NICs, and Mellanox Connect X-5 40 Gbits/s NICs. If you use Mellanox NICs, you should install the Mellanox OFED as described in DPDK's documentation. If you use Intel NICs, you should insert the IGB UIO module and bind your NIC interface to it (e.g., using the script ./dpdk/usertools/dpdk-setup.sh).

To enable Jumbo Frames for higher throughput, first enable them in Linux on the relevant interface like so:

ip link set eth0 mtu 9000

Then use the (host_mtu) option in the config file of each runtime to set the MTU to the value you'd like, up to the size of the MTU set for the interface.

Directpath allows runtime cores to directly send packets to/receive packets from the NIC, enabling higher throughput than when the IOKernel handles all packets. Directpath is currently only supported with Mellanox ConnectX-5 using Mellanox OFED v4.6 or newer. NIC firmware must include support for User Context Objects (DEVX) and Software Managed Steering Tables. For the ConnectX-5, the firmware version must be at least 16.26.1040. Additionally, directpath requires Linux kernel version 5.0.0 or newer.

To enable directpath, set CONFIG_DIRECTPATH=y in build/config before building and add enable_directpath to the config file for all runtimes that should use directpath. Each runtime launched with directpath must currently run as root and have a unique IP address.

This code has been tested with an Intel Optane SSD 900P Series NVMe device. If your device has op latencies that are greater than 10us, consider updating the device_latency_us variable (or the known_devices list) in runtime/storage.c.

Ensure that you have compiled Caladan with storage support by setting the appropriate flag in build/config, and that you have built the synthetic client application.

Compile the C++ bindings and the storage server:

make -C bindings/cc
make -C apps/storage_service

On the server:

sudo ./iokerneld
sudo spdk/scripts/setup.sh
sudo apps/storage_service/storage_server storage_server.config

On the client:

sudo ./iokerneld
sudo apps/synthetic/target/release/synthetic --config=storage_client.config --mode=runtime-client --mpps=0.55 --protocol=reflex --runtime=10 --samples=10 --threads=20 --transport=tcp 192.168.1.3:5000

Ensure that you have built the synthetic application on client and server.

Compile the C++ bindings and the memory/cache antagonist:

make -C bindings/cc
make -C apps/netbench

On the server, run the IOKernel with the interference-aware scheduler (ias), the synthetic application, and the cache antagonist:

sudo ./iokerneld ias
./apps/synthetic/target/release/synthetic 192.168.1.8:5000 --config victim.config --mode spawner-server
./apps/netbench/stress antagonist.config 20 10 cacheantagonist:4090880

On the client:

sudo ./iokerneld
./apps/synthetic/target/release/synthetic 192.168.1.8:5000 --config client.config --mode runtime-client

You should observe that you can stop and start the antagonist and that the synthetic application's latency is not impacted. In contrast, if you use Shenango's default scheduler (sudo ./iokerneld) on the server, when you run the antagonist with the synthetic application, the synthetic application's latency degrades.