Generic System Calls for GPUs
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1 Generic System Calls for GPUs Ján Veselý*, Arkaprava Basu, Abhishek Bhattacharjee*, Gabriel H. Loh, Mark Oskin, Steven K. Reinhardt *Rutgers University, Indian Institute of Science, Advanced Micro Devices Inc., University of Washington, Microsoft Inc.
2 Towards heterogeneous computing CPU Acc GPU Application ISCA
3 Programs require system services CPU: function process(port, file) { data, response_data, response = malloc(); data = recvmsg(port); idx = get_idx(data); response_data = pread(file, idx); response = process(response_data, data); log( request processed\n ); sendmsg(port, response); } free(data, response_data, response); ISCA
4 Programs require system services CPU: function process(port, file) { data, response_data, response = malloc(); data = recvmsg(port); idx = get_idx(data); response_data = pread(file, idx); response = process(response_data, data); log( request processed\n ); sendmsg(port, response); Memory allocation } free(data, response_data, response); Memory allocation ISCA
5 Programs require system services CPU: function process(port, file) { data, response_data, response = malloc(); Memory allocation data = recvmsg(port); Network idx = get_idx(data); response_data = pread(file, idx); response = process(response_data, data); log( request processed\n ); } sendmsg(port, response); free(data, response_data, response); Network Memory allocation ISCA
6 Programs require system services CPU: function process(port, file) { data, response_data, response = malloc(); Memory allocation data = recvmsg(port); Network idx = get_idx(data); response_data = pread(file, idx); Storage response = process(response_data, data); log( request processed\n ); } sendmsg(port, response); free(data, response_data, response); Network Memory allocation ISCA
7 Programs require system services CPU: function process(port, file) { data, response_data, response = malloc(); Memory allocation data = recvmsg(port); Network idx = get_idx(data); response_data = pread(file, idx); Storage response = process(response_data, data); } log( request processed\n ); sendmsg(port, response); free(data, response_data, response); Terminal/Storage Network Memory allocation ISCA
8 Programs require system services CPU: function process(port, file) { data, response_data, response = malloc(); GPU: Memory allocation data = recvmsg(port); Network idx = get_idx(data); response_data = pread(file, idx); Storage response = process(response_data, data); } log( request processed\n ); sendmsg(port, response); free(data, response_data, response); Terminal/Storage Network Memory allocation ISCA
9 Computation can be offloaded CPU: function process(port, file) { data, response_data, response = malloc(); GPU: GPU MANAGEMENT GPU INVOCATION GPU KERNEL data[] = recvmsgs(port); copy_to_device(data[]); gpu_get_idx(&idx[], data[]); copy_from_device(idx[]); for (d in data) response_data[] = pread(file, idx[i]); copy_to_device(response_data[]); gpu_process(&response[], response_data[], data[]); copy_from_device(response[]); Kernel 1 idx[i] = get_idx(data[i]) Kernel 2 response[i] = process(response_data[i], data[i]) log( requests processed\n ); sendmsgs(port, response[]); ISCA
10 GPUs are tightly integrated Unified virtual memory (UVM) HSA, CUDA UVM, OpenCL SVM CPU GPU cache coherence HSA, CCIX, Gen-Z ISCA
11 UVM and cache coherence ease programmability CPU: GPU: GPU MANAGEMENT function process(port, file) { data, response_data, response = malloc(); data[] = recvmsgs(port); GPU INVOCATION GPU KERNEL copy_to_device(data[]); gpu_get_idx(&idx[], data[]); copy_from_device(idx[]); for (d in data) response_data[] = pread(file, idx[i]); copy_to_device(response_data[]); gpu_process(&response[], response_data[], data[]); copy_from_device(response[]); Kernel 1 idx[i] = get_idx(data[i]) Kernel 2 response[i] = process(response_data[i], data[i]) log( requests processed\n ); sendmsgs(port, response[]); ISCA
12 UVM and cache coherence ease programmability CPU: GPU: GPU MANAGEMENT function process(port, file) { data, response_data, response = malloc(); data[] = recvmsgs(port); GPU INVOCATION GPU KERNEL copy_to_device(data[]); gpu_get_idx(&idx[], data[]); copy_from_device(idx[]); for (d in data) response_data[] = pread(file, idx[i]); copy_to_device(response_data[]); gpu_process(&response[], response_data[], data[]); copy_from_device(response[]); Kernel 1 idx[i] = get_idx(data[i]) Kernel 2 response[i] = process(response_data[i], data[i]) log( requests processed\n ); sendmsgs(port, response[]); ISCA
13 UVM and cache coherence ease programmability CPU: function process(port, file) { data, response_data, response = malloc(); data[] = recvmsgs(port); GPU: GPU MANAGEMENT GPU INVOCATION GPU KERNEL copy_to_device(data[]); gpu_get_idx(&idx[], data[]); copy_from_device(idx[]); for (d in data) response_data[] = pread(file, idx[i]); copy_to_device(response_data[]); gpu_process(&response[], response_data[], data[]); copy_from_device(response[]); Kernel 1 idx[i] = get_idx(data[i])? Kernel 2 response[i] = process(response_data[i], data[i]) log( requests processed\n ); sendmsgs(port, response[]); ISCA
14 Next step is system services ISCA
15 Next step is system services Memory allocation HSA, CUDA ISCA
16 Next step is system services Memory allocation HSA, CUDA Printf HSA, OpenCL, CUDA ISCA
17 Next step is system services Memory allocation HSA, CUDA Printf HSA, OpenCL, CUDA Academic research GPUfs [Silberstein, ASPLOS 13], GPUnet [Kim, OSDI 14], SPIN [Bergman, ATC 17], ISCA
18 Some services can be invoked from GPU CPU: function process(port, file) { data, response_data, response = malloc(); gpu_process(port, file, response[], response_data[], data[]); free(data, response_data, response); } GPU: void gpu_group_process(port, file) { data = Grecv(port); idx = gpu_get_idx(&idx, data); response_data = Gread(file, idx); GPUnet GPUfs CUDA response = process(response_data, data); Gprintf( request processed\n ); } Gsend(port, response); ISCA
19 Previous solutions took the first steps ISCA
20 Previous solutions took the first steps Subsystem specific ISCA
21 Previous solutions took the first steps Subsystem specific Specialized, restricted functionality ISCA
22 Previous solutions took the first steps Subsystem specific Specialized, restricted functionality Custom API/semantics ISCA
23 Our work takes the next step ISCA
24 Our work takes the next step GENEric SYStem call interface Efficient direct-to-os communication ISCA
25 Our work takes the next step GENEric SYStem call interface Efficient direct-to-os communication Allows all system calls implementable for GPUs 79% of all system calls ISCA
26 Our work takes the next step GENEric SYStem call interface Efficient direct-to-os communication Allows all system calls implementable for GPUs 79% of all system calls Original OS (Linux) semantics POSIX -like ISCA
27 Our work takes the next step GENEric SYStem call interface Efficient direct-to-os communication Allows all system calls implementable for GPUs 79% of all system calls Original OS (Linux) semantics POSIX -like Available on github ISCA
![Genesys subsumes previous work (and more) CPU: GPU: GENESYS function process(port, file) { gpu_process(port, file, response[], response_data[], data[]); } void gpu_process(port, file) { data,](/docs-images/87/96384983/images/28-1.jpg "response_data, response = malloc(); data = recvmsg(port); idx = get_idx(data); response_data = pread(file, idx); response = process(response_data, data); log( requests processed\n ); sendmsg(port,")
28 Genesys subsumes previous work (and more) CPU: GPU: GENESYS function process(port, file) { gpu_process(port, file, response[], response_data[], data[]); } void gpu_process(port, file) { data, response_data, response = malloc(); data = recvmsg(port); idx = get_idx(data); response_data = pread(file, idx); response = process(response_data, data); log( requests processed\n ); sendmsg(port, response); } free(data, response_data, response); ISCA
29 Ideal system services properties Familiarity Known semantics ISCA
30 Ideal system services properties Familiarity Known semantics Flexibility Do not restrict programmers Adaptability Adapt to workload needs ISCA
31 Flexibility in application interface Invocation granularity ISCA
32 Flexibility in application interface Invocation granularity Observed ordering ISCA
33 Flexibility in application interface Invocation granularity Observed ordering Blocking vs. Non-blocking ISCA
34 Flexibility: Any thread can invoke system call GPU execution hierarchy ISCA
35 Flexibility: Any thread can invoke system call GPU execution hierarchy Workitem (thread) ISCA
36 Flexibility: Any thread can invoke system call GPU execution hierarchy Workitem (thread) Workgroup (thread group) ISCA
37 Flexibility: Any thread can invoke system call GPU execution hierarchy Workitem (thread) Workgroup (thread group) Kernel kernel workgroup workgroup workgroup workgroup ISCA
38 Flexibility: Any thread can invoke system call GPU execution hierarchy Workitem (thread) Workgroup (thread group) Kernel kernel workgroup workgroup workgroup workgroup Wavefront (warp) HW specific! Do not expose! ISCA
39 Flexibility: Any thread can invoke system call GPU execution hierarchy Workitem (thread) Workgroup (thread group) Kernel Invokes system call kernel workgroup workgroup workgroup workgroup Wavefront (warp) HW specific! Do not expose! ISCA
40 Flexibility: Ordering can be relaxed (group) Strict ordering Both barriers Relaxed ordering Remove one barrier Before read After write workgroup ISCA
41 Flexibility: Ordering can be relaxed (group) Strict ordering Both barriers Relaxed ordering Remove one barrier Before read After write write workgroup ISCA
42 Flexibility: Ordering can be relaxed (group) Strict ordering Both barriers Relaxed ordering Remove one barrier Before read After write write workgroup ISCA
43 Flexibility: Ordering can be relaxed (group) Strict ordering Both barriers Relaxed ordering Remove one barrier Before read After write write workgroup ISCA
44 Flexibility: Ordering can be relaxed (group) Strict ordering Both barriers Relaxed ordering Remove one barrier Before read After write write workgroup ISCA
45 Flexibility: Ordering can be relaxed (group) Strict ordering Both barriers Relaxed ordering Remove one barrier Before read After write write workgroup ISCA
46 Flexibility: Ordering can be relaxed (group) Strict ordering Both barriers Relaxed ordering Remove one barrier Before read After write write workgroup ISCA
47 Flexibility: Ordering can be relaxed (group) Strict ordering Both barriers Relaxed ordering Remove one barrier Before read After write write workgroup ISCA
48 Flexibility: Allow non-blocking invocation Blocking invocation Wait for result Non-blocking invocation Return value collected later or not at all workgroup ISCA
49 Flexibility: Allow non-blocking invocation Blocking invocation Wait for result Non-blocking invocation Return value collected later or not at all write workgroup ISCA
50 Flexibility: Allow non-blocking invocation Blocking invocation Wait for result Non-blocking invocation Return value collected later or not at all write workgroup ISCA
51 Flexibility: Allow non-blocking invocation Blocking invocation Wait for result Non-blocking invocation Return value collected later or not at all write workgroup ISCA
52 Flexibility: Allow non-blocking invocation Blocking invocation Wait for result Non-blocking invocation Return value collected later or not at all write workgroup ISCA
53 Flexibility: Allow non-blocking invocation Blocking invocation Wait for result Non-blocking invocation Return value collected later or not at all workgroup ISCA
54 Flexibility: Allow non-blocking invocation Blocking invocation Wait for result Non-blocking invocation Return value collected later or not at all workgroup ISCA
55 Ideal system services properties Familiarity Known semantics Flexibility Do not restrict programmers Adaptability Adapt to workload needs ISCA
56 Adaptability in implementation ISCA
57 Adaptability in implementation Don t waste resources Syscall light applications Important for heterogeneous systems Share power and energy budget ISCA
58 Adaptability in implementation Don t waste resources Syscall light applications Important for heterogeneous systems Share power and energy budget Use as many resources as possible Syscall heavy applications ISCA
59 Implementation GPU CPU Syscall area Main Memory ISCA
60 Implementation 1. Fill Parameters 2. Send Interrupt (suspend) 3. Process Interrupt 4. Execute System call 5. Fill return value 6. Wake up wavefront (if suspended) GPU CPU 1 Syscall area Main Memory ISCA
61 Implementation 1. Fill Parameters 2. Send Interrupt (suspend) 3. Process Interrupt 4. Execute System call 5. Fill return value 6. Wake up wavefront (if suspended) GPU 2 CPU 1 Syscall area Main Memory ISCA
62 Implementation 1. Fill Parameters 2. Send Interrupt (suspend) 3. Process Interrupt 4. Execute System call 5. Fill return value 6. Wake up wavefront (if suspended) GPU 2 CPU 3 1 Syscall area Main Memory ISCA
63 Implementation 1. Fill Parameters 2. Send Interrupt (suspend) 3. Process Interrupt 4. Execute System call 5. Fill return value 6. Wake up wavefront (if suspended) GPU 2 CPU Syscall area Main Memory ISCA
64 Implementation 1. Fill Parameters 2. Send Interrupt (suspend) 3. Process Interrupt 4. Execute System call 5. Fill return value 6. Wake up wavefront (if suspended) GPU 2 CPU Syscall area Main Memory ISCA
65 Implementation 1. Fill Parameters 2. Send Interrupt (suspend) 3. Process Interrupt 4. Execute System call 5. Fill return value 6. Wake up wavefront (if suspended) GPU 2 6 CPU Syscall area Main Memory ISCA
66 Genesys works on off-the-shelf hardware ISCA
67 Genesys works on off-the-shelf hardware AMD FX-9800P 4 CPU cores, 8 CUs (gpu cores) Share 15W of TDP 16GB DDR4 RAM ISCA
68 Genesys works on off-the-shelf hardware AMD FX-9800P 4 CPU cores, 8 CUs (gpu cores) Share 15W of TDP 16GB DDR4 RAM GPU L2 cache is CPU coherent GPU L1 coherence is handled in software Provides CPU GPU atomic operations ISCA
69 Ideal system services properties Familiarity Known semantics Flexibility Do not restrict programmers Adaptability Adapt to workload needs ISCA
70 Genesys supports wide range of use cases Storage ISCA
71 Genesys supports wide range of use cases Storage Networking ISCA
72 Genesys supports wide range of use cases Storage Networking Memory Management ISCA
73 Genesys supports wide range of use cases Storage Networking Memory Management Device Control ISCA
74 Storage workload grep ISCA
75 Storage workload grep Parallelize across number of files ISCA
76 Storage workload grep Parallelize across number of files Exploit high throughput storage devices ISCA
77 Storage workload grep Parallelize across number of files Exploit high throughput storage devices Each workitem (thread): open, read, write(stdout), close ISCA
78 Time (s) Storage workload grep Parallelize across number of files Exploit high throughput storage devices CPU original Genesys workgroup CPU openmp (4T) Genesys workitem Lower is better Each workitem (thread): open, read, write(stdout), close grep ISCA
79 Networking workload memcached ISCA
80 Networking workload memcached Heterogeneous application ISCA
81 Networking workload memcached Heterogeneous application CPU and GPU work on the same data SET CPU GET GPU, CPU ISCA
82 Networking workload memcached Heterogeneous application CPU and GPU work on the same data SET CPU GET GPU, CPU Each workgroup (thread group) recvmsg, write(stderr), sendmsg Parallelize; hash, lookup, data copy ISCA
83 Operations per second Networking workload memcached Heterogeneous application CPU and GPU work on the same data SET CPU GET GPU, CPU Each workgroup (thread group) recvmsg, write(stderr), sendmsg Parallelize; hash, lookup, data copy Throughput memcached CPU GPU Genesys GPU without syscalls Higher is better hits misses ISCA
84 Time (ms) Networking workload memcached Heterogeneous application CPU and GPU work on the same data SET CPU GET GPU, CPU Each workgroup (thread group) recvmsg, write(stderr), sendmsg Parallelize; hash, lookup, data copy Latency memcached CPU GPU Genesys GPU without syscalls 2.5 Lower is better hits misses ISCA
85 Memory management miniamr Algorithm includes memory allocator Adaptive mesh refining Enable judicious use of system resources Accelerator multiprogramming Coarsening workitems (threads) madvise(madv_dontneed) ISCA
86 Device control ioctl Audio devices USB devices Network devices GPU! ISCA
87 Device control ioctl Audio devices USB devices Network devices GPU! Display frame buffer ISCA
88 Device control ioctl Audio devices USB devices Network devices GPU! Display frame buffer ISCA
89 Conclusion Generic POSIX -like system calls for GPUs are viable Improvement in programming environment leads to new applications and improved performance of traditional ones All code is available on github, hosted by AMD ROCm project ISCA
90 Disclaimer & Attribution The information presented in this document is for informational purposes only and may contain technical inaccuracies, omissions and typographical errors. The information contained herein is subject to change and may be rendered inaccurate for many reasons, including but not limited to product and roadmap changes, component and motherboard version changes, new model and/or product releases, product differences between differing manufacturers, software changes, BIOS flashes, firmware upgrades, or the like. AMD assumes no obligation to update or otherwise correct or revise this information. However, AMD reserves the right to revise this information and to make changes from time to time to the content hereof without obligation of AMD to notify any person of such revisions or changes. AMD MAKES NO REPRESENTATIONS OR WARRANTIES WITH RESPECT TO THE CONTENTS HEREOF AND ASSUMES NO RESPONSIBILITY FOR ANY INACCURACIES, ERRORS OR OMISSIONS THAT MAY APPEAR IN THIS INFORMATION. AMD SPECIFICALLY DISCLAIMS ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE. IN NO EVENT WILL AMD BE LIABLE TO ANY PERSON FOR ANY DIRECT, INDIRECT, SPECIAL OR OTHER CONSEQUENTIAL DAMAGES ARISING FROM THE USE OF ANY INFORMATION CONTAINED HEREIN, EVEN IF AMD IS EXPRESSLY ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. ATTRIBUTION 2018 Advanced Micro Devices, Inc. All rights reserved. AMD, Radeon, the AMD Arrow logo and combinations thereof are trademarks of Advanced Micro Devices, Inc. in the United States and/or other jurisdictions. Other names are for informational purposes only and may be trademarks of their respective owners. ISCA
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