lowRISC tagged memory preview release

April 13, 2015

We’re pleased to announce the first lowRISC preview release, demonstrating support for tagged memory as described in our memo. Our ambition with lowRISC is to provide an open-source System-on-Chip platform for others to build on, along with low-cost development boards featuring a reference implementation. Although there’s more work to be done on the tagged memory implementation, now seemed a good time to document what we’ve done in order for the wider community to take a look. Please see our full tutorial which describes in some detail the changes we’ve made to the Berkeley Rocket core, as well as how you can build and try it out for yourself (either in simulation, or on an FPGA). We’ve gone to some effort to produce this documentation, both to document our work, and to share our experiences building upon the Berkeley RISC-V code releases in the hopes they’ll be useful to other groups.

The initial motivation for tagged memory was to prevent control-flow hijacking attacks, though there are a range of other potential uses including fine-grained memory synchronisation, garbage collection, and debug tools.

Please note that the instructions used to manipulate tagged memory in this release ( ltag and stag ) are only temporary and chosen simply because they require minimal changes to the core pipeline. Future work will include exploring better ISA support, collecting performance numbers across a range of tagged memory uses and tuning the tag cache. We are also working on developing an ‘untethered’ version of the SoC with the necessary peripherals integrated for standalone operation.

If you’ve visited lowrisc.org before, you’ll have noticed we’ve changed a few things around. Keep an eye on this blog (and its RSS feed) to keep an eye on developments - we expect to be updating at least every couple of weeks. We’re very grateful to the RISC-V team at Berkeley for all their support and guidance. A large portion of the credit for this initial code release goes to Wei Song, who’s been working tirelessly on the HDL implementation.